Ilya Talman, Author at Roy Talman & Associates

The Real Key To Getting A Job Working With AI

Posted on June 24, 2019

Without question, one of the most popular topics in our business right now is how to get a job working with artificial intelligence / machine learning.

At one level, we have clients that want cutting-edge, top-of-the-line researchers. Fair enough. However, there is one issue we’ve seen arise in lot of people who received their advanced degrees in artificial intelligence between 2010 and 2016: They might have problems in applying their knowledge in a world that moves very fast, where they are asked to apply well-known ML approaches rather than inventing new ones.

Believe it or not, a lot of the fundamental ideas behind artificial intelligence, particularly the mathematical models, were developed in the 1960s. Unfortunately, there were two critical challenges facing us at the time: 1) Computing power was very expensive and 2) partly because of number one, there was not enough data.

Fast forward to 2011 where we had an explosion of data availability. Thanks to video games and other popular applications creating demand, a whole industry of GPUs came about to produce very elaborate, very complex graphics. The real breakthrough in 2011 came when two graduate assistants working with computer scientist Geoffrey Hinton figured out how to code GPUs to look at pictures. That was the beginning of a trend that would basically break the dam wide open where suddenly, you could look at millions of available pictures and have a way of processing them, even identifying each picture by image.

Since then, we’ve seen the amount of computing dedicated to machine learning doubling every quarter (per Ray Kurzweil). Every vendor has an offering in machine learning and is clearly working on a chip to do it better.

So while people realized how to code GPUs in 2011, that was merely the beginning. Today, you have people such as Elon Musk saying he doesn’t need to use GPUs from years ago because he’s just produced a chip that is much better for machine learning in an autonomous driving setting. He has designed a chip with the target of it being the most customized, energy-efficient chip in the history of machine learning. Musk describes his chips as 10 times better than the previous generation of chips that we were using until now. Still, Tesla does not slow down. They are continuously evolving these chips.

So we’re getting to the point where more machine learning projects are becoming feasible. It’s cost-efficient to get data and cheap enough to build the intelligence into machine learning applications so that you can start using it – typically not instead of, but in addition to people. Expect that we will have some kind of machine learning in practically everything we touch. And that probably will mean that we will need many more people working on it.

Talman Advantage #6: The Technical Expertise Clients Highly Respect
How many account managers within a recruiting firm have technical PhDs and MSs? Not many. Yet, you’ll find several of them at Roy Talman & Associates, which our clients in the technological space have come to highly respect over the course of 30+ years. No wonder they respond quickly in real time. And when we suggest the creation of a new position just for you, they seriously consider our suggestion at a minimum and frequently call us to discuss further.
See yourself represented from a higher place right from the very beginning. Talk to Talman first.

How PhDs Can Shift Gears And Bridge The Gap
Here’s the challenge: At the moment, a variety of people who work in machine learning believe that they are going to be developing new, advanced machine-learning algorithms. A good idea in theory. In reality, that is often not the case. Most challenges lie in figuring out how to apply the vast number of very sophisticated, freely available algorithms that already exist. For example, you really don’t need to reinvent an open-source library like TensorFlow – you need to learn how to use it.

Then you have the other part of the equation, which is the data. Beyond collecting data, which takes significant work, you need to be able to clean the data to make it usable. This calls for a lot of software engineers, data engineers and project engineers to figure that aspect out.

The good news? For the PhD who understands how to best apply existing complex algorithms in machine learning and arrive at usable, clean data, the career opportunities should be plentiful.

The need for talent and capacity for growth in the area of AI is enormous, even though the capability to fill these positions has not been fully realized.

In fact, the opportunities are so vast that we’re even seeing the potential to apply machine learning to animal populations, not just of the human variety. Here’s a story to illustrate: Not long ago, there was an amusing story in the Wall Street Journal on how hard it is to build facial recognition system for pigs and cows. Pigs and cows! Why would we even want to bother with such a thing?

Well, consider this: If a farmer can have better facial recognition per animal, they can keep track of them even better, they can determine which animal is sick, they can see whether their particular activity is ample enough and more. It turns out that if you can do facial recognition on a herd of cows, then you can start monitoring the herd at the level of each individual animal. So as funny as it sounds to worry about a new kind of facial recognition for pigs and cows, it offers a new level of productivity and efficiency. But when the person building the application was interviewed, he complained how hard it is to get those animals to stand still or to face him in the right profile.

Whereas microchipping can be expensive, if all you need to do is take a picture, that in and of itself is extremely cost-efficient. Facial recognition represents the beginning of being able to collect data and once you do that, you might be able to recognize all kinds of other activities and traits. Even if your cows are not very cooperative.

If we stand to have many more people working in AI, how can you increase the opportunity that you’re one of them? Talk to Talman first. Roy Talman & Associates can help prepare you for the types of projects that might be suited to your background without forcing you into a less-than-ideal fit. Instead, we’ll tell you what you need to work on to elevate your skill set and position yourself to adapt comfortably into the growing areas of machine learning you can thrive within.

AI Graduating Beyond “Side Project’ And Moving Up The Priority List

Posted on June 14, 2019

While there has been an issue with how expensive it is to build machine learning systems and “feed” them, there’s good news to be had in that we foresee the cost of building these systems and feeding them continually going down. And as that happens, their usefulness and applicability is only going to grow. We’re entering a new phase where it’s not about more hardware or lines on a chip of silicone, but instead more about the cost per recognizing a photo, cost per recognizing a moving image or cost of recognizing speech.

As machine learning becomes more and more like electricity, it will represent a growing percentage of the vast majority of available jobs. To what degree these are new jobs, old jobs, reformulated jobs or new tasks for people who are doing certain jobs isn’t abundantly clear.

That said, what we are seeing is that, at the top of the hiring pyramid, perhaps five years ago, there was room for 1,000 people using machine learning algorithms, developing new ones, developing new hardware, etc. Because it was expensive and the knowledge was so expensive, it would take substantial time and effort to train people to do certain things. So, the bright, young sophomore was sitting there trying to decide: Do I go into machine learning or do I go into aerospace? And if going into aerospace was perceived as a better prospect career-wise, that’s what this person was going to do. However, if they heard how much money a classmate made or how much fun a friend had working in machine learning, perhaps he or she would spend the next two years learning about that.

There’s a real cost of getting into certain fields, which is a challenging decision people have to make. Some of this is influenced by how much people make in that field. The more they make, the more it will attract new people to enter that field, which might result in more and more new people not making as much money. Nonetheless, there will be more of them. This cumulative snowball effect is driven by the fact that the cost of deploying useful machine learning is continually dropping.

This means many more projects in machine learning make sense and many more people are required. There’s never a shortage of people, just that sometimes there are a whole bunch of projects that don’t get done because they are too expensive vis-a-vis their benefit. Still, if the price of implementation of these projects goes down, many more of them will get implemented and our society will receive a great benefit.

Talman Advantage #7: We Already Know Many People At The Top
The built-in advantage of being a more specialized recruiter for over three decades is that Roy Talman & Associates established many strong relationships with senior leaders in the C-suite and Director level. How do we truly leverage that? Prior to your interview, we can provide you terrific insight on the person’s background, the questions they’re likely to ask you and even a few clues into why prior candidates were likely rejected.
A recruiter that equips you with more information in advance of the interview? That just might make all the difference – if you talk to Talman first.

As the cost of AI comes down and becomes more accessible, these types of projects will move up on a company’s priority list. It will no longer be a “side gig” to work on machine learning for 20% of your time. It might become closer to 80% of your time.

As we’ve mentioned in previous posts, Masayoshi Son, the CEO of conglomerate SoftBank, essentially says that the entire business is a bet on machine learning. Google is a company that thinks of itself as a machine learning company too. These are some of the most successful and far-looking organizations out there, which tells us many more companies need to get on board.

In fact, we should be building out our machine learning functionality much faster than it took electricity to propagate through the business world. It took electricity about 40 years to accomplish this feat and the key problem with electricity was that the existing factories built for steam engines were built vertically. It took enough of a benefit for electricity to get to the forefront where people started knocking down those tall factories. I suspect that our pace of innovation of machine learning will be dramatically faster.

What About The Pace Of Incoming Talent?

The pace of the talent coming in is such that there may be a top position in an organization that pays them over $500,000 a year while an average salary comes in between $125,000 and $175,000, which is nothing to sneeze at.

As a result, that’s the level of compensation you’re looking at to induce people into an AI learning curve. The more people going through the learning curve, the more productive they are. What really needs to happen is that we shorten the learning curve.

Step one is moving from the present-day state of learning with a complicated, 200-line Python code to get any kind of functionality out of ML to a state where writing five lines of Python code gets useful results.

Step two is building the infrastructure to collect the data. This does take quite a while. Take the healthcare business, where getting medical data is very tricky. Due to HIPAA and other factors, you don’t have an ideal environment where there are systems to easily collect data, so you have to train people to use various technologies to capture data. At the moment, the typical doctor is not equipped to gain much use from large data, but that’s the point we’ll get to eventually. It’s the pace at which we learn that can be accelerated. Room for growth? Absolutely.

The bottom line here is that the cost of computing is still collapsing and that means that the quantity of work in computing is growing exponentially. It also means there will be a tremendous amount of projects moving forward that we couldn’t even compute before.

A career working in AI interests you. You’re committed to reaching a point where you’re called upon to get stronger results out of your code more efficiently as well as understand how to best apply collected data. What needs to happen from here is a straightforward conversation with one of the most highly specialized tech recruiters in the industry at Roy Talman & Associates. Together, we can make a plan that leverages the strengths you have and enhances those skills that demand improvement. Don’t leap into your next career move hoping for the best. Talk to Talman first. And give yourself the best foundation for ongoing success there is.

Small H1B Visa Change May Mean Big Help For Those With Advanced Degrees

Posted on June 6, 2019

As we’ve written a few times on the challenging, ever-evolving H1B Visa process for employers and international candidates, a minor but interesting change to the H1B Visa program has occurred that’s worthy of you to be aware of if you hire people from that program.

There are two types of H1B Visas:

There are 20,000 visas for people with master’s degrees and PhD’s from U.S. universities (MS/PhDs). In addition, there are 65,000 visas for people who do not have master’s degrees or PhD’s from U.S. universities. These visas are open to the rest of the field.

In the past, if you happened to have a master’s degree or PhD from a U.S. institution, you participated in the 20,000 visa application process first. Those who qualified but were not chosen in the first lottery had their applications thrown into a big pot with the remainder of the applications and there was a follow-up lottery to draw from 65,000 available “regular” visa applications.

Once the lotteries were run, those who got into the lottery were evaluated for accuracy. But the presumption was that everybody who applied was going to get their H1B Visa.

The “minor change” introduced by the administration is a change to the order in which pools are processed. Now the first pool is going to be the general pool. After that, if there are any people with master’s degrees and PhD’s from US schools who did not get picked in the lottery, they move on to a second lottery only open to them. This also depends on how many applications there are of both kinds – such as master’s and PhDs or non-master’s and non-PhD’s.

Talman Advantage #5: A Real Partner With A Plan
When a recruiter talks to you on the phone for 20 minutes just once, there’s only so much they know about you beyond the resume. On the other hand, Roy Talman & Associates will work with you to gain a robust understanding of your skill set, goals, work style preferences and more. Then, rather than “blasting” your resume out to the hiring universe with random results, we’ll make a plan with you on what order we will present you to various firms that we feel are a best fit.
Your career deserves more than a quick chat. Partner with a recruiter who can help you feel more in control of the process – as you should be. Talk to Talman first.

For example, let’s say that there are 50,000 people with master’s/PhD’s and 100,000 people without who are in the overall pool.

In the new system we would expect that 50/150 = 33% of MS/PhDs, around 21,666, will be selected in the first round. The remaining 28,334 MS/PhDs will participate in the 2^nd round resulting in 20,000 more selected. Overall 41,666 MS/PhDs will be selected.

Using the same assumptions, in the prior system, 20,000 of MS/PhDs are selected in the first round and 130,000 would participate in the 2^nd round resulting in 30/150 * 65,000 = 13,000 more MS/PhDs selected for the total of 33,000. As you can see given these initial assumptions the MS/PhD group getting H1B will grow by 8,666 (from 33,000 to 41,666) or by 26%.

Our clients are probably more likely today to be more willing to sponsor somebody with a master’s degree or PhD from a U.S. institution. So my expectation is that there might be some increase in the number of people with an advanced education who will be getting their H1B. Once they get their H1Bs, a number of our clients may be interested in these people and the process of transferring H1Bs will be relatively shorter and easier than getting an H1B Visa in the first place.

We’ll be keeping a close eye on this update to the process in the months to come in terms of those who won the lottery. Then people can start working after October 1 when their H1B Visa officially kicks in.

No matter what process is right for you, whether it involves navigating the H1B Visa route or not, the very best first step for a solid recruitment strategy is to talk to Talman first. We’ll discuss your hiring goals and the type of candidate you’re seeking to make an immediate impact in your environment. With over 30 years of experience and a vast network, our team at Roy Talman & Associates may be already well connected to just the special technical talent you’re looking for.

Non-Compete? No Problem. Maximize Your Time Between Jobs.

Posted on May 20, 2019

As we’re frequently dealing with senior people in high-frequency trading shops and hedge funds, it’s not uncommon to see many of them face a non-compete situation that can last as long as 18 months. This person may be privy to a process that is material to generating revenue, so a certain level of protection needs to be put in place promptly.

Not all non-competes are written exactly the same and the meaning of them can change.

Fortunately, it’s one of the areas at Roy Talman & Associates that we’ve had a lot of experience with and as such, we work with our candidates in helping them figure out how to confront the situation. Especially since every situation is different.

One of the more popular temporary resolutions to a non-compete is to take a sabbatical. The person winds up spending a year or more doing something else. We’ve seen several people take at least three years’ worth of sabbaticals over a decade due to the non-competes they have.

Some people decide that they’re going to get into a particular hobby, like windsurfing. Others might choose to work on their house. Some see it as an opportunity to spend more time with their children.

There’s another way to utilize this time, which is to evaluate your next move from a career standpoint and sharpening up your skill set. That’s where a variety of senior-level people have approached our firm for a more in-depth conversation. If you’re in a similar situation where you recently resigned or were let go, a non-compete may still be very much in place. So you may want to explore what others have done in your circumstances.

Talman Advantage #4: Better Positioning For Your Best Opportunity
The reality is that, in so many situations, that “perfect job opportunity” may not be formally listed by a company. In that instance, where some may simply fire your resume off to an HR person’s email and hope for the best, Roy Talman & Associates takes a more creative and purposeful approach.
If an opening isn’t currently available that’s an ideal match for you, we’ll discuss the kind of role with you that you would be interested in and potentially prepare and present a very specific case to that particular firm to create a unique role for you. That’s called a recruiter that goes further for you – and why you need to talk to Talman first.

Lay the groundwork now with a conversation with our team about what you ideally want to achieve in the next chapter of your career. What technologies await you to learn? What industries are worth exploring that you may not have previously considered thanks to an influx of new technologies in the cloud or machine learning?

If you’re in the area of high-frequency trading or hedge funds, finding yourself with “forced time off” due to a non-compete may be something you experience more than once in your career. When the time comes and you find yourself with a substantial amount of time between now and your next position, you don’t have to feel lost. By discussing your goals from a career and lifestyle standpoint right now with a specialized technical recruiter such as Roy Talman & Associates, you can be ready for the next era of change.

If you’d like to evolve your skill set during this time off, we’ll talk about what’s required in order to bring yourself up to speed and the aptitude tests you’ll need to pass with flying colors. If you’d like to enter a totally new environment, we’ll help you envision the change in culture and management style from your previous workplace to prepare yourself for, should you be hired. And if you’d like to take a trip halfway around the world, we’ve seen our share of candidates do that too.

Seize the opportunity to find your best individualized path to professional and personal clarity during your time between positions. Talk To Talman First.

Readying Your Company For A Machine Learning Talent Pipeline

Posted on May 2, 2019

For a very long time, we’ve heard about shortages of people with specific skills but most of those skills in question tend to be on the newer side of the spectrum. For example, if you listen to people at Google and Amazon, they’re in dire need for machine learning talent. Unfortunately, that represents a small percentage of people in the field. There are just so many PhD’s with an education in machine learning over the last three years. Considering that most of the practical machine learning advances happened in the previous five years, this defines an incredibly small number of people.

Meanwhile, we’re approaching a situation where more companies are dipping their toes in the water and finally making an effort to develop skill sets for their people in machine learning. There’s a terrific course by Andrew Ng on Coursera that is a non-technical description of machine learning from the business point of view where he discusses where things are in machine learning today and what companies interested in developing machine learning talent should foresee.

Ng is telling companies that, if they’re genuinely committed to it, it’s going to take two to three years to develop their Machine Learning (ML) teams and achieve some, initially small, project wins to demonstrate to the rest of the organization what ML can do for their firm.

Now, we’ve been talking about this influx of machine learning talent for several years – longer than expected, in fact. That said, we should expect a fair number of companies in a variety of industries finally begin to move toward building AI machine learning teams and starting machine learning projects.

They’re already realizing that for every machine learning expert, they need a lot of software expertise that coincides with a number of them looking to get much more aggressive about building things in the cloud.

The Cloud And Machine Learning Talent “Bottleneck”

Everybody is trying to get through the door at the same time, which creates a bit of a problem. While you have a fair number of colleges trying to educate people on newer technologies such as the cloud and ML, change doesn’t happen overnight. The more aggressive coding camps are helping, but these are challenges that will take a while to resolve.

In the meantime, we are in the early stages where many companies don’t exactly know what they need to do to succeed on the ML front. They do know that building an AI team is a start as they can’t ignore the significant technological shift and a greater maturity of the field, with more tools that are easier to use.

From a hiring perspective, as companies better appreciate what needs to be accomplished on each project, they will come to realize that perhaps they don’t absolutely need to hire someone with a PhD from Carnegie Mellon or someone working with a division of Google. After all, if that’s the only person who can solve your problem, you may have a very tough time getting them into your environment. But there’s some good news.

Talman Advantage #3: The Preparation For The Interview You Deserve

You can’t go into an interview armed with only a resume to represent you. Roy Talman & Associates gets you ready for the experience with a far more in-depth level of preparation, including an evaluation of your skills in light of what today’s marketplace demands.
Through testing on certain subjects and measuring your scores against what our clients expect, you’ll be able to head into the interview knowing so much more. You’ve come too far to settle for anything less. So make sure you talk to Talman first.

The Pool May Be Expanding

One of my favorite authors, Ray Kurzweil, recently mentioned in a speech that the amount of computing dedicated to machine learning has been doubling every quarter. If that trend continues, we’re going to begin seeing it everywhere very, very quickly. And with the expansion of talent dedicated to this area of learning, the good news is that you probably won’t need to compete for precisely the same people that Google is snapping up the minute they get PhD’s. That’s where things will get really interesting.

As this technology grows to permeate more of our economic lives, companies will need to invest in machine learning and take advantage of exponentially more useful machine learning tools within the next couple of years or they may be seriously left behind. Case in point: I was listening to an interview with Masayoshi Son, the CEO of SoftBank Group and a manager of $100 Billion Vision Fund, where he said he is “all in” on machine learning in all forms. He has invested billions of dollars in machine learning because he believes it is going to be used everywhere and used for almost everything, from chip companies to autonomous car driving.

What Represents A Good Start For Your Company?

Turning first and foremost to a recruiter with a long-established foothold in technical areas such as Roy Talman & Associates can help, especially as we have a finger on the pulse of what’s new and next. We’re currently in discussion with a number of companies who have approached us for help in developing a presence in ML. Typically this comes about because an individual who has known us for a number of years is now a true expert in ML, with the capability to build something substantial.

Some of these individuals aren’t necessarily trying to be presented at various companies and receive offers, but they are looking for counsel for when the right opportunities and applications for their skill set come along.

That’s a case of being in the right place at the right time for candidates and companies alike. With the soon-to-be proliferation of machine learning expertise in many fields, don’t muddle along with the status quo for too long. Make the right move and Talk To Talman First. Because this is one trend we expect to not only impact our business but quite possibly your own as well.

How Candidates Can Keep Their Learning Curve Ahead Of Accelerating Technology

Posted on April 18, 2019

In the last 18 months, with a variety of tech companies facing a solid amount of turnover – as in people leaving after only a year or two – you’d imagine that many candidates don’t need to put a whole lot of work into the entire interviewing process. They’d just use the most recent version of their resume, add one line describing where they’ve been working and bingo! They’d get 15 offers, right?

Actually, that’s not what we’re observing.

On the contrary, the people these companies want in technology or trading – whether it be in Silicon Valley, on Wall Street or in Chicago – are being viewed as very similar and, in fact, less attractive. Why? Because far too many of these people cannot follow through the technical interview process that the market demands. They simply are not that well prepared to handle the questions and challenges given to them during this process.

Putting Yourself In Better Alignment To Move Forward

If we dig deeper as to why some candidates don’t get far enough into the technical interview process, we find that, in some situations, the individual doesn’t have enough of an appreciation in how far software technology has moved over the last five years and its various directions.

Fortunately, there is a way to overcome this and it starts by being a student of the latest technology, trends and processes.

For example, step outside of your own industry for a moment. In what industries, do you see several of the more exciting advancements occurring? Hypothetically speaking, if you were to transition into that industry, how much know-how might be required to seamlessly make that move? What companies appear to be at the forefront of these technological advancements? What do you know about their leadership? Have they been recently covered in a series of articles you can research to gain a sense of where their commitments for the long-term are? What positions do they appear to be hiring for on a consistent basis?

Similarly, what kind of tech leaders do you admire and what inspires you about the work they’re doing? How much of a distance lies between where you are today and what you can learn tomorrow in order to get closer to entering this type of environment? It may not be as far away as you think.

In fact, some candidates hold themselves back before they even begin this level of research for their career growth. Why? They make the mistake of saying, “Well, I’m working somewhere that is more into maintaining old technology, so it’s hard for me to know about new things from here.” While that’s a challenge, you can’t simply give up and let your workplace potentially limit your ability to absorb new understanding, such as the different thought processes on the proper architecture for systems that have come along.

After all, in addition to the merit of continuously evolving your skill set and knowledge, who is to say that a new leader takes charge at your company, causing a shift where he wants to jumpstart new projects in an area of technology that few have studied…except you? Suddenly, you may find yourself with quite the opportunity just by staying on top of new technologies.

Talman Advantage #10: Stronger Negotiating Power On Your Side
The terms of your employment aren’t to be taken lightly. With our 30+ years of industry expertise, Roy Talman & Associates has a keen eye for detail during negotiations. In fact, if the help of an attorney is required for this purpose, we can suggest one. Can any recruiter offer the same result?
Don’t wonder about the outcome. Stand with a recruiter who has the track record to negotiate firmly in your favor. Make the right call and talk to Talman first.

Here’s why it’s so important to keep your understanding moving forward, even if your company is all too comfortable running in place with current systems.

For one, technology is accelerating, which means it now takes fewer years to effectively be left behind if a candidate does not evolve their learning. The half-life of this knowledge used to be five years or so – in other words, after five years, a person could find themselves passed by if they did not enhance their technical knowledge. Now we’re seeing that window shrinking once again. Expect to have only two or three years to further your understanding of emerging technologies and trends.

To illustrate this point, I was particularly surprised by talking to a CTO of one of our clients recently, who said about a very capable technologist, “He was truly state-of-the-art as of five years ago. Ideally, we need somebody who is state-of-the-art as of five minutes from now.”

In other words, the greatest risk is being wonderfully content with what you know now versus taking the opportunity to make your skill set far more marketable. Don’t wait for your current employer to make that move for you.

As you do keep up with accelerating technology and gain an understanding of how best to integrate it into certain systems, you may position yourself well to help companies more easily migrate from an older system to a new one. Until now, perhaps some leaders have assumed that the process is going to be tedious and expensive. But what if you could show them that this transition isn’t quite as slow and painful as they might expect? Perhaps being presented with a real plan for taking a system from point A to point B represents the gentle push that some leaders have been waiting to see. And you might just be the person to deliver it.

If The Future Is Now, Where Can You Most Likely Find It?

We’ve obviously talked about why you shouldn’t rely exclusively on whether or not your company embraces new technology. However, some certain technology companies can be the exception, where you’ll see that change is baked right into their structure. Take a company like Amazon, for example, with their Amazon Web Services growing at such a rapid rate. They know that they need to continually add new functionality because customers are buying the service and older things naturally die off (look no further than Sears for a worst case scenario of a company that saw things die off without aiming to replace them). In this situation, you’re working for a team focused on the future of technology, enabling you to do your work and maintain your pole position in the marketplace.

Managers want somebody who will demonstrate that they are keeping up with the latest technology and staying on the cutting edge. Therefore, it’s going to require a process that helps bring candidates and hiring managers closer together to increase the likelihood that more candidates are fully equipped and ready to deliver what the “best of the best” companies demand.

As a reaction to the challenges candidates face in developing both technical and interviewing skills, we’ve created a process we call The Talman Way. Even before you’re definitely looking to make a change, meet with Roy Talman & Associates and you’ll discover what you need to bring your skills up to speed, whether that entails reading books on interviewing or practicing taking online tests on a particular skill. And that’s just the beginning. Considering it’s the next chapter of your career we’re talking about, why trust it to just anyone? Talk to Talman first.

Prepping Your Skills For The Machine Learning Revolution

Posted on April 8, 2019

In one of our recent posts, we wrote about the coming revolution in machine learning that candidates have to prepare themselves for. In truth, we’ve heard a lot of talk about it for several years now, but we still haven’t seen a lot of activity utilizing machine learning in many companies. Does this mean it’s all a myth that’s about to come and go? Hardly. We firmly believe that, unlike the artificial intelligence craze, the machine learning revolution is going to continually gain steam.

The best way to judge the success of a trend such as machine learning is by how easy or how difficult is it to implement.

If you need to have a PhD from Carnegie Mellon in Artificial Intelligence to get anything done, those projects will be far and few between. The moment you get to the point where you can accomplish a lot of results with a solid technologist who can learn how to use the tools – and with those tools being ever-more powerful and easier to use – we’ll see the technology expand beyond the small group that has been using it.

In many situations, this probably will entail building new infrastructure. The data that you need and the ability to handle that data doesn’t exist today. You cannot easily graph modern machine learning technology onto existing infrastructure.

That’s why so many of these projects wound up going to the cloud. There is a fierce and productive competition in the cloud between Microsoft, Google, Amazon, IBM and so many others. By competing for new projects, these companies are continually improving the environment, making it easier to build new systems and making those systems more likely to be successful. It means we’re in a virtual cycle where the more something is done, the easier it gets to do it. It’s one of the more exciting areas in machine learning technology.

Who Are The Ideal Candidates For Machine Learning That Companies Want?

From our perspective, companies want a machine learning expert with a recent degree. However, for every one of those, they also realize that they need to hire a lot of technologists who allow them to have the framework within which to collect the data. Then they have the ability to collect and get the sources of the data. When the data arrives, it needs to be cleaned and maintained for people in machine learning to handle it. The trend I would expect is, as machine learning tools become more and more powerful, people will need less and less extreme statistical expertise in machine learning in order to get results.

Talman Advantage #1: Our Connections Run Deep
Why is it so critical that Roy Talman be the first recruiter you talk to? Before your resume is casually distributed to others, it’s important to understand how valuable it is to work with someone who brings a credible and highly reputable network of hiring managers. We’ve cultivated relationships with these managers for over 30 years – in fact, many of them were our candidates at one point.
But if you distribute a resume before we can leverage such connections to identify the best firm and role for you, it may be very difficult for us to help you further. So before you send out a resume, talk to Talman first!

The analogy I like to use is that when relational databases originally were thought of, very few people knew how to use them. Today, most software engineers now do SQL, even though they don’t necessarily know how to prove all the mathematical theorems that underline the algebra of SQL and data manipulation. Think of it in this way – you don’t need to be an internal combustion engine expert to drive your car. Yes, there was a time when you needed to know a great deal about it because your engine would break down and you had to fix it.

So if you can talk to your machine learning system and explain to it what you want done, that’s ideally what companies are after.

For recurring tasks, it’s not enough to have a certain amount of knowledge trapped in your brain. You actually have to convey it to a machine in a clear way and have a bigger picture for the business so it knows what is doable and what is not. That’s why so many companies that we deal with, when we talk about senior level roles, insist on knowledge of current technology. They just don’t think a manager who is not aware or fluent in the latest technology should be trusted with making technical and managerial decisions.

How can you put your skill set in sync with where machine learning is headed? Talk to Talman first. A conversation with the technical recruiting experts at Roy Talman & Associates can help gauge where your background best aligns and where some critical skills gaps may be occurring that you need to close efficiently. Instead of guessing and hoping where you should devote your learning – or worse yet, doing nothing at all other than maintaining what you know right now – we can engage you in a process that factors in your goals, your ideal environment, preference of management style and more. So as technology further evolves, you can ensure you do the same in a place you’re profoundly comfortable working in.

“Home Grown” Talent Versus Importing It

Posted on March 19, 2019

Many times, we’re preconditioned to think of hiring for talent that’s right in our own backyard. It’s convenient and let’s face it – there’s less to consider in the way of relocation expenses if it’s local and “home grown.” However, if we’re going to always be looking not only for the next great candidate but also the “next Silicon Valley,” maybe we should take a closer look at how places like Silicon Valley have actually obtained its talent.

The reason Silicon Valley has been successful over the last 20-30 years is that it’s been very effective at sucking in brainpower, first from all over the U.S. and then worldwide. Its greatest brains haven’t necessarily been right around the corner. In order to continually do this over as many years as Silicon Valley has, you have to create an environment where you have winning companies and a lot of very rich people.

Once you have the momentum going continually attracting the most capable people on Earth, you will create a very wealthy environment. Not only is Silicon Valley very wealthy but also very demanding. I’ve referred to this race as “The Lottery” where some people wind up hitting it really big, others still do really well and others basically say, “Well, this is a rat race and I don’t want to run myself into the ground on Startup #7 seeing as my prior six didn’t work out.”

So what does this have to do with the rest of the population of a given area like Silicon Valley? The “Silicon Valley”-like environment creates an extremely high cost of living. People who lived there for a long time have difficulty deciding to move. In reality, what they do is they give up their lifestyle. You have people living in much smaller older homes and commuting much further out because, somehow, in their mind, that’s what they’ve always done. The cost of living is really determined mostly in those areas by the cost of real estate.

For people who are in the “Haves” category, the restriction of new construction or any kind of other real estate restrictions doesn’t hurt them because they already own their houses or condos. As such, there is really no push in these areas thus far to lower the cost of real estate. The only way to lower the cost of real estate is to build more. The only way to build more is to create an environment where it makes sense to build more. And that is not the case in a lot of these areas.A

Talman Advantage #2: We See The Complete Picture Of Who You Are

At Roy Talman & Associates, we don’t just see you as a resume or even a candidate to fill an open job. Instead, we’ll ask to meet you because we want to get to know you on a deeper level – that includes your current skills, your knowledge of certain subjects, your special expertise, your work style and the environments in which you believe you thrive.

Compare that to others. But always talk to Talman first.

“Have-Nots” On The Move

The net result is likely to be that the “Have-Nots” will progressively find that they’re getting pushed out. To some degree, we’re seeing such a trend even in Chicago – perhaps on a lesser scale, but nonetheless you have areas where the values of real estate have gone up, which results in people who can’t afford to stay there getting pushed out. We will likely see this in quite a few areas – not just Silicon Valley or Manhattan.

The solution for this is for the “Have-Nots” to say, “OK, we’re going to go to places where we can have more.” So as you look at the cost of living, the question is, where can you make a living? If you go to Toledo, Ohio, your $60,000 a year gets you a very nice lifestyle. This may be the opportunity that companies in certain markets are looking for to attract ever more capable people. It’s only when it reaches a point where the cost of living gets to be so high and the density is so unbearable that the companies say, “Well, maybe we can still manage to be as productive or somewhat productive in much lower cost of living situations.”

It’s then that you see Manhattan investment banks moving their operations to Arizona or companies moving their headquarters to Dallas where the cost of living is much lower. Or you begin to see a slightly different version of Silicon Valley being created in Austin, Texas, where people are working on very similar challenges from a technology standpoint.

It’s also why Amazon now will have a second headquarters (even though they won’t be in New York for it anymore). Most people think that when Amazon goes to northern Virginia, it’s because they’ll expect to find all of the talent they’ll need in that area. In reality, a vast majority of the talent that Amazon found in Seattle…was talent they brought to Seattle. History will likely repeat itself here. It’s not that the talent is already there and free for the taking. The move is more to diversify their collection points for talent.

Similarly, for all that has been written about the influx and expansion of Silicon Valley companies into the Chicago market, it is due to a variety of factors – not purely that all of the talent these companies are aiming to attract is already “home grown.” In fact, just as the case is in many other markets, trying to obtain very specialized talent often calls for widening the scope beyond a local view. Even companies such as Google and Facebook are discovering that this talent needs to be imported from other places – which, in fact, is not any more unusual than many other growth-oriented markets.

What this calls for is an eye for recruiting the very best talent locally and outside of the given market, so that companies aren’t limited in their growth. They can focus on connecting with the highest quality candidate that fits the role, their culture, their values and their goals. That’s the unrestricted position that a firm with over 30 years of experience, such as Roy Talman & Associates, can put your company in. To experience what having that advantage feels like, talk to Talman first.

Building Stronger Tech Worker Relationships In A New Era Of Activism

Posted on February 28, 2019

Recently, Google had a massive walk-out – about 20,000 employees – over its handling of cases of sexual harassment and misconduct. It’s part of a shift we’re seeing in tech environments in what some are branding, “tech worker activism.” Employees in the tech space seem louder than ever, essentially saying, “You may be Google, but we have the rights and power to get the things we want.”

People are quick to talk about broken company cultures, but in my view, it’s not purely about that. There are a variety of poorly managed cultures in many places where employees still aren’t walking out the door.

No, here’s what really drives the activity: Any time you have organizations that generate as much wealth as Silicon Valley has generated, that wealth is fairly widespread. In the process, you create an environment in which all kinds of constituents are going to demand something from these organizations. One simple understanding is because these companies can afford it as they have ample resources (i.e. Google).

Therefore, it’s my assumption that we’ll only see more movements toward companies that have accumulated sufficient wealth and seemingly aren’t doing right by their employees in some form or fashion. We will see more activism and more litigation. Whether it’s going to be specifically against Facebook, Google, Amazon or another prominent name, any kind of “winner” in this society is going to be under pressure, either to satisfy additional demands or share the wealth/resources they’ve accumulated to a much greater degree.

Talman Advantage #9: A Smoother Transition Into The New Environment
Thanks to close rapport with senior managers and relationships with clients that have lasted for many years, Roy Talman & Associates has the in-depth knowledge of a firm’s work atmosphere that few can bring to the table.
As a result, we can often provide guidance on what to expect from the culture you’re about to join, which hopefully makes your integration into that environment all the more seamless.
Make your first days in a new role better than you ever expected by talking to Talman first.

Externally, these companies are really good at delighting their customers and maintaining high profit margins. However, the internal situation at times tells a different story – such employees represent a type of “customer” that needs to be heard too. The more that a company’s talent perceives itself to be in a position to make demands, the more demands will be made. And these demands can run the gamut from mishandling of sexual harassment cases to complaints that there is not enough space per person to work.

Consequently, as your organization scales upward and accumulates wealth, you can expect that a spotlight will shine on not only your culture but also your level of consistent communication with employees on the issues that are of the highest importance to them. Don’t kid yourself into thinking that this challenge is only reserved for the likes of massive companies such as Google or Facebook.

Thinking optimistically, an environment of ever-increasing employee demands doesn’t have to be something you constantly fear. In fact, if the challenge can be embraced by your management team and handled successfully, it can be an opportunity to strengthen the relationships you’ve strived to nurture with your team. Communicate with them early and often. Listen to team members when they bring forth concerns. Collaborate with them to address their needs. Demonstrate actions that show you’ve taken the appropriate steps to meet those needs. It doesn’t mean you have to do everything a group of employees demands but ignoring such demands is hardly a suitable option either.

All of which could lead to great things in the name of your recruitment and retention efforts too.

Talman Talks Tech Predictions For 2019

Posted on February 13, 2019

Before I get started about what I foresee in the tech space for the coming year, let me share my favorite line about predictions, from Niels Bohr: “Prediction is very difficult, especially if it’s about the future.”

So while you may take some of these predictions with a grain of salt, I do think there are several trends we will be paying closer attention to in 2019 from a technological perspective.

From where I sit, I believe we probably will see continued escalation and consumption of technology by people who have already been consuming technology at a high level as it is.

In New York, that likely means companies will try to get on top of applying the latest technology to consume dramatically higher volumes of data: Expect increased investment in distributed computing, the Cloud and new languages like Go or Scala. At the same time, companies will aim to consume more individualized data as opposed to pre-packaged data, which should lead to building more complex systems. Machine Learning is one of the most powerful new technologies and its growth requires dealing with ever larger data sets.

A Few More Self-Driving Taxis Hit The Streets

No, 2019 won’t be the year that we see a massive shift to autonomous driving vehicles but we should continue to see steps forward on this front, particularly with self-driving taxis. I was listening to an interview of the gentleman who is running Waymo, the subsidiary of Alphabet, focusing on driverless cars. It was clear that he views the path to mainstream adoption of self-driving vehicles as a marathon, not a sprint. It could take decades and it’s not clear as to when we will have ability to drive in sleet, snow and in dense areas.

That said, the end of 2018 saw Waymo launching a taxi service for self-driving cars in a test market. The cars aren’t completely driverless and do have drivers behind the wheel for now as a safety mechanism, but as these advanced vehicles become “smarter” for all types of scenarios on the road, you can be sure that driverless vehicles will slowly but surely increase. The self-driving car is no longer an if and is rather a matter of where and when.

Wider Digitalization Of Health Care

It used to be that people would say things like, “What’s the point of doing genomic sequencing? What’s that going to do?”

Well, now that we’re getting to the point of sufficient quantities of genomic sequencings collected, we’re finding that as more data is collected of polygenic (caused by interactions of multiple genes) scores, we can group people in percentiles for complex phenomena like going to college. We can now say that people that rank in the lowest 10% are five times less likely to go to college than people ranked in the top 10%. This is without knowing anything about the parents or anything else and strictly using genomic data.

What we’re going to see as the price of genomic sequencing continues to go down, instead of a million sequences, we’ll start seeing hundreds of millions of sequences. From this, we can combine the data from these many sequences to actually find a lot of useful information that is not 100% predictable, but certainly predictable to an extent.

For example, I was reading about a gentleman quoted in the Wall Street Journal, who said that when he looked at his genomic sequence, he had a 94% likelihood of being obese. He remarked that if his parents knew this information at birth, perhaps they would have approached child rearing differently based on their child’s predisposition to gain weight.

Expect to see a much greater investment in genomic sequencing in 2019 as it continues to make sense for a broader audience.

Talman Advantage #8: True Help To Hit The Ground Running
With an offer coming, do you have a solid understanding of what you’ll be doing in the first 6 months? The first year? Having placed a variety of senior people at each client’s firm, Roy Talman & Associates can help you clarify a whole lot about the environment you’re about to join, your role and the true expectations of your new manager.
A recruiter without the overwhelming credibility that we have may not be able to shed as much light on what’s in store for you on Day 1 and beyond. So get the insight you need and talk to Talman first.

Greater Adoption Of Machine Learning Techniques

Right now, I believe the vast majority of people think machine learning is brain surgery. Yet, in practical terms, it’s a net of collecting data and figuring out how to clean the data. The algorithms themselves are essentially free for the taking, but you need people with a clue of how to do that. It’s a situation where if three people know how to do it, it’s brain surgery. If 1,000 people know how to do it, it’s still quite tricky. If 500,000 people know how to do it, it gets to be where things are getting done and cost-effectively – and I think we might finally be entering this area next year.

Will there, in turn, be a great opportunity for more hiring in the machine learning space? Right now, there’s just not enough people who appreciate what it takes.

For example, I spoke with someone in New York who is talking about building a new kind of infrastructure capable of handling a vast amount of data that’s greater than what their current systems are capable of handling.

To accomplish this, you can’t merely expand the current system. You need to build a new system. Once you build the new system, you then need to feed the data into the system. Then you need to build the software infrastructure on top of the data to be able to sift through the data and then pipe it into machine learning algorithms. So ,machine learning is like the oracle that needs to be fed all kinds of data in order for you to receive an answer. But if you cannot get to the oracle, you won’t get the wisdom. So it’s building the road to the top of the hill where the oracle is.

Machine learning is fundamentally recognizing patterns that are already in the data. For that you need to have relatively clean data and a lot of it. Very few organizations have that data to date. Plus, their first reactions are to try to figure out how to use the data they have, which doesn’t always work.

This calls for more software engineers who know how to utilize machine learning technology.

Once the machine learning algorithms are fairly well established, it’s a matter of just digging more data. So essentially you have an entire ecosystem of tools that need to be created, then polished so that they’re usable for people. But once they do use them, the information starts propagating. This is easier to handle in the cloud than on your own hardware. If you have a situation where you need 100,000 computers to work on something for an hour, it’s silly and impractical to buy computers to do that task for yourself, but in the cloud it makes a lot of sense. So whether it’s via Google cloud, Amazon cloud or Microsoft cloud, we’re going to see machine learning drive a good portion of the cloud business going forward.

What do you predict in 2019 for the state of hiring in your business? If it involves hiring for the “best of the best” tech talent, don’t wait long to plan for that situation. Talk to Talman first. Roy Talman & Associates can factor in your overall business goals to help you identify the type of extraordinary talent that just may provide you many happy returns for this year and beyond.