Jul 25, 2018
Technology and the jobs that go with it are evolving exponentially faster. How can new grads and seasoned pros alike be prepared for the jobs of tomorrow? How does Microsoft hire the brightest minds to work on leading edge tech? We ponder these questions and more with Dave Wecker, Architect at Microsoft’s Quantum Computing team, and Tyler Roush, of Microsoft’s talent sourcing team. Dave gives us a peek into his work on the frontier of quantum computing, and Tyler shares what it’s like to source talent for an international dream team. Then, we sit down with Microsoft engineer Raymond Uchenna Ononiwu to get his tips on landing a Microsoft internship and how to turn that into a full-time job offer.
Jason Howard: You’re listening to the Windows Insider Podcast and I’m your host, Jason Howard. This is Episode 17: Jobs of Tomorrow. Technology and the jobs that go with it are evolving exponentially faster. How can new grads and seasoned pros alike be prepared for tomorrow’s jobs in tech? How does Microsoft hire the brightest minds to work on leading edge tech? We ponder these questions and more in this episode.
In case you didn’t know, the Windows Insider Program runs quite a few awesome contests and they are only available to Insiders. So that’s my shameless plug – if you aren’t yet a Windows Insider, go to our website and register. It’s free, it’s easy, and you become a part of a global community shaping the future of Windows.
OK, onto the show!
Jason Howard: First up, we have special guests from Microsoft’s Quantum Computing team to talk about life on the cutting edge and what Microsoft looks for in candidates for jobs on the frontiers of innovation. Dave and Tyler, welcome to the show. Would you please introduce yourselves for our audience?
Hi, I'm Dave Wecker. I'm the Quantum Architect and my job is to pull all the pieces together from the very top which is the software, we normally do all the way down to the materials, the fridges, the devices that we put in our labs all over the world. So, I spent a lot of time on an airplane going from lab to lab.
Tyler Roush: My name is Tyler Roush. I work with our talent sourcing team and I've been working with Dave for the last two years but most of my job is trying to understand what they do as much as possible and identify some of the skills that we need to come on to Microsoft to help build a quantum computer.
Jason Howard: So he's doing a cool stuff, and you're getting people to come in and do the cool stuff.
Tyler Roush: Exactly.
Jason Howard: Awesome. So Dave, we start with you. Can you help us understand in kind of layman's terms what quantum computing actually is.
Dave Wecker: Yeah it's actually fairly straightforward, if you think of it compared to classical computing. Classical computing we have bits, and a bit is zero or one. The qubit which is the basic unit in quantum computing is also zero and one but it can be zero and one at the same time. It's actually a little more than that because there's more information than just the zero or one in there. So, you can do a lot of computing with a single qubit. If 32-bits holds one number, let's say on your phone, that number can be from zero to four billion, 32 qubits can hold four billion numbers at once. So, all of a sudden, you're doing computation on a massive amount of information at one time, this unlocks a whole bunch of possibilities for what you can do computationally that you can't do with a classical computer.
Jason Howard: So, what are some of the possibilities that kind of like get you going, things that you've found and they have expanded your mindset and way of thinking about it when it comes to what quantum computing will enable us to do?
Dave Wecker: Well there's some poster children we use, things that are good examples of what you can do. A lot of people bring up cryptography, Shor’s algorithm but to be honest that's not our focus, it's not the type of thing that we want to do in terms of solving problems for the world and doing things for Microsoft that we think are worth doing and are important.
So, I'll start with a very mundane one, which is fertilizer. Fertilizer is something that is extremely expensive for most of the world and the reason is it takes a process that uses a lot of energy, a lot of pressure, high temperatures to make and so a lot of the emerging world can't buy fertilizer because it's out of their price range, because of the amount that it takes.
We're talking on the order of five percent of the natural gas on the planet every year is consumed to make fertilizer, three percent of the total energy output of the planet. On the other hand, there's a little, tiny anaerobic bacteria that sits in the root of all plants, that sits there happily at room temperature and room pressure, low energy and it takes air and breaks the nitrogen bond and makes fertilizer, makes ammonia.
We know we can do this, because it can do it, but we can't analyze the actual molecule that's in there, that causes the fertilizer to be made. We can't because it uses quantum effects that can't be analyzed on classical machines but can on quantum computers. So, you could make low-cost, artificial fertilizer if you had a quantum machine to analyze it.
Same problem for global warming. We could build a algorithm that looks at the global warming problem, and we know that you could make a paint that we paint everything in the world and it just sucks the carbon out of the air.
All of these take on the order of 200 logical qubits. So, we're not talking about giant machines, and we'll be able to solve first-world problems that we have no way of approaching today.
I'll give one more, is transmission lines the United State, 15 percent of our energy output is lost by just sending the energy from one place to another. If we can make room temperature superconductors, again type of problem we can analyze on a quantum computer, we'd get that 15 percent back. That's a large amount of energy that we lose every year.
Jason Howard: Just between the actual cost of generating the energy, obviously the extra work that goes directly, that gets put into trying to make it more efficient, to transfer it, you solve those problems and you kind of work backwards and there's kind of savings all the way up the chain until you know the actual energy creation process.
Dave Wecker: Exactly.
Jason Howard: Wow. These are like some real-world things that you're potentially solving here, this isn't just some hypothetical, "Hey, we think we could potentially try something crazy." Like they are actual problems that exist right now, then obviously there are some understanding behind, "Hey, once we crack this Quantum computing thing and get further with it, we're going to be able to tackle some pretty big things with it."
Dave Wecker: So we view it just like you view a co-processor in Azure—the way we use specialized GPUs, we use FPGA's, we use various processors in Azure to solve specialized problems. Like in machine learning, for example, the Quantum computer is not very good at the things the classical machine is good at. But it is good at the types of things that we're describing. By making it a co-processor in Azure, you wind up getting the best of both. You can do super-computing like classical work in Azure, and then offload the work that is best done on a quantum computer to it and now you can solve definitely real-world problems as soon as the technology becomes available.
Jason Howard: So, obviously knowing the problems that the world is facing, we could get into an all-day conversation about ideas you have, problems you want to tackle and things like that. But when it comes to doing your day to day job, what's your favorite part of it, what actually gets you up in the morning and gets you excited to work on these problems?
Dave Wecker: That's easy. The group I work with is some of the best people in the world in all the various areas you need. Everything from quantum physics, to materials design, to refrigeration of cryogenic systems, to cryogenic classical computing, to on and on and on, and I get free training.
I'm at the point now where if I wanted to, I could probably go back and easily get a PhD in various fields, because I've had the best people in the world hand me all the textbooks and say, "Here, read this, now read this, now do this." I get to work in the labs, I actually get to do these quantum experiments with the professionals that are there, I get to write software that analyzes the data, I get to work with building and growing materials that we use to make the devices.
So, I'm like a kid in a candy store, I get to do everything you could think of from top to bottom and I get to go all over the world at the same time and work with, like I said, the best people I've ever met.
Jason Howard: So, I want to highlight something because this definitely caught my attention as we've been talking here. So, you're not only working on the software side of things, you're creating the technology and the hardware being used to do this computing. So, you're building the platformsm on which you're then building the software on top of, to gain the outputs that you need to drive some of this technology?
Dave Wecker: That's completely correct. So, my backgrounds is electrical engineering originally. I also have a business degree, and so I actually work on what makes sense as a company that Microsoft should be doing and how we should do this and how we plan over the next decade of bringing this to fruition. And it's also the type of thing where it's like a Bell Labs or a NASA project. I can't go and buy the wires that I need to go from 15 Milli-Kelvin to 4 Kelvin. These are extremely cold, 100 times colder than outer space, and you can't even make normal wiring work, so we have to develop our own. We have to do our own connectors. We have to do our own boards, our own chips, our own materials, top to bottom. So, it's something where we really have to build all of it before we can write the software that goes on top of it.
Jason Howard: I thought it was bad trying to keep a computer cold to do basic overclocking.
Dave Wecker: Exactly. It's also the case that we really don't have to wait for the hardware. We can simulate a quantum computer up to a certain size, beyond a certain size is impossible on a classical machine, but up to about 30 qubits, it's not very hard.
So, we ship a Quantum Development Kit that we make available to the public, it's free, it's open source, it's available to the world. In that kit, you have a quantum simulator that let you write the algorithms and run them on the simulated quantum computer just like they would run on the real one. It would just have more qubits when we're done.
So, we have a very large software development effort that's going on in parallel with all the hardware and the devices, so when the hardware shows up, the software will be ready for it.
Jason Howard: Wow. Tyler.
Tyler Roush: Yes.
Jason Howard: Got to couple of questions for you.
Tyler Roush: Absolutely, let's go.
Jason Howard: Can you share a bit about what it's like to hire for the Quantum Team? Obviously, you have some pretty smart folks you're trying to bring in if they're writing their own software, creating their own hardware, obviously there's a lot of travel required to connect the dots with smart people all around the globe. This really is the cutting edge of the cutting edge. How is hiring for this Quantum Computing Team, what is it like? How do you source talent when you're talking about this level of expertise and knowledge that's required?
Tyler Roush: Sure, it's challenging, but it's the right type of challenge that I like to go after. So, when we think about the Seattle market in terms of talent, there's Amazon, there's Microsoft, it's a growing ecosystem of companies that are in the area. So, finding software engineers is relatively frequent for us to be able to go out and find people in the area, who are already located here. Even the Bay Area being really close. My experience with the Quantum Team the last two years has been a lot of international travel as well.
Most of these conferences, because it's such a small community, there's only a few that everyone will attend, and they're also located all over the world. So, Europe has been a location the last few years in trying to identify people. Then, also the types of people that are in the field right now, because it's just transitioning now into more of a product environment or heavily in academia.
So, when you think about having a conversation about career with someone, that conversation looks a lot different if they're coming from Amazon or another industry company that we're familiar with versus someone who might be a professor at an academic institution. The considerations they have to make, if they have PhD students, the considerations they have to make, if they're on tenure track, and so just that career conversation has been a really interesting perspective to have to learn the last two years.
Jason Howard: It sounds like there's a lot to be done between the theoretical side of things where people are exploring and trying to forge new ground and make a name for themselves. As opposed to jumping into what would be a more professional track, where you go and you're pouring your expertise into a company, actually doing some of the development there. How does the split work between doing it in a more academic environment versus a professional environment, like here at Microsoft?
Tyler Roush: So, from the conversations that I've had in the past with candidates, it's different, and I think there's a little bit of education that usually happens in the conversations as well. So, when people think about an industry company, they usually think about very product-oriented goals, tight deadlines, and in research, there's a lot of autonomy that you have to be able to draw your own research, and essentially go after topics that you really find interesting.
In Microsoft Research as well as the Quantum Computing Group, that's still the case.
So, just having to really educate people about the experience of what it's like working at Microsoft. Some of the biggest advantages, as opposed to being a professor, is you don't have to raise money. When you are a professor, you have to go and find grants to your students all the time. That's a lot of work that professors don't tend to get associated with. But, for us in working for Microsoft, there's a lot more time that you could actually spend researching the topic that you want to research, whether some of the materials work that Dave was mentioning.
That was actually what I was thinking of as well when he gave his answer there. Quantum materials development, I think, is one of the most interesting areas that we'll see in quantum computing in the future, just because there's this convergence of the physical, digital, and biological worlds happening. I think quantum computing is really going to drive that more than ever. As we've seen things like retail go automated and digital more and more, it'll be about the biological worlds coming into some of the alloy development, or fertilizer work.
Dave Wecker: I'd also like to add that we have realized to go further in this, we really need to work tightly with academic institutions. So, as such, we've supported the labs at various locations especially in Delft in the Netherlands, in Copenhagen in Denmark, Purdue in the United States, Sydney in Australia.
At those sites, we've also created a Microsoft lab. So, you can be a Microsoft employee, work at the lab side-by-side with the academic lab, and actually go back and forth between the two. The principal investigators actually run both labs that we have at each site. So, this lets us also recruit locally. It lets us work very tightly with the university on the research they're doing, as well as working towards engineering the solutions we need that we could then bring back to Redmond, and actually do work here.
Jason Howard: Oh, interesting. So, at least from what I'm picking up from the conversation so far, there's this nice balance that has been achieved, at least within this small community of-- being small currently, right? Who knows what the future holds? I expected to get much bigger over the course of time. It sounds like the candidates that exists in this field, some of them have some practical world experience of doing some development at a company, be it Microsoft or elsewhere, obviously. But, it sounds like it's not just people who've got electrical engineering degrees, right? Obviously there's computer sciences involved, but it sounds like there's a lot of physics involved here, probably some chemistry along the way. It isn't just, "Hey, I've been sitting at a keyboard punching away and learning a programming language." There's way more to this than that.
Dave Wecker: Very true. I've worked in a lot of fields that intersect with computer science over time, and we find it's actually easier to take computer science people and teach them, in this case the physics, versus taking physicists and teaching them computer science.
So, we don't try to turn the physicists into computer scientists, we instead take computer science, embed them in the labs with the physicists, and have them help. So, we've written entire software infrastructure just for running lab equipment, called Q codes, which is available open source on the net, that will run all of this various equipment from Python, let you run from a Jupyter Notebook, or anything internally.
You can also use the Quantum Development Kit that I mentioned at the beginning, and that is an environment that uses all the.NET languages. It also interfaces to Python as well and Jupyter Notebooks, but it actually is a new language called Q#, which we've shipped, that makes quantum computing as easy to implement as any of the other languages in computer science.
Jason Howard: Wait, so you're telling me there was a new programming language- excuse me programming language written?
Dave Wecker: For quantum.
Jason Howard: Wow.
Dave Wecker: It's shipped at under Visual Studio. It runs under VS code, and actually if, Miles will mention, if we go to microsoft.com/quantum, that's everything we do in quantum. It's under there including how to get the development kit. You can also get to our blogs where we have the information on examples and samples and, for instance, all the different things in chemistry I mentioned: the materials, the examples of software written in Q#, and libraries that you can use to solve these kinds of problems.
Jason Howard: Wow, and the spreadsheets. So, Tyler I got another question for you. Obviously we've talked about some of the educational background that is involved in these type of fields and we listed some of those just a moment ago. What could be the potentially overlooked skills or personality type qualities in some of these candidates? Is there anything specific that you're finding in the candidates for these roles that would help somebody thrive in this type of environment?
Tyler Roush: I don't know that I could say that there's a hard skill associated with someone that does or is more apt to be in the quantum field. Honestly, I think our evangelism team is doing an excellent job when you talk about it being a growing field. They're working with a lot of universities and more and more so every day in trying to implement quantum education as part of the work that happens in masters and PhD programs now and specifically around our Q# programming language. So, University of Bristol, there was an event last month that we held where students were coming up and asking us about our Q# language.
To Dave's point, trying to teach computer scientists Q# and Quantum programming through normal mechanisms that computer scientists would use is the ultimate goal, so that you don't have to have as much inherent knowledge on physics, on quantum development in order to participate in the field.
Jason Howard: So, I've got a question here that I'm super curious about. Say you were interviewing David here for Laurel, said he didn't work at Microsoft, what kind of questions would you ask him?
Tyler Roush: That's a great question I have to admit here. So, I guess my answer to that would be a little different than you might expect. So, obviously quantum computing is a very technical field, so most of the conversations that I have revolve around career and personal goals more so than the hard technical skills and what they're involved in. What I typically like to do is try to understand what someone might be working on in their publication work, start the conversation there as far as what their career topical interests and just beginning to understand the person and what they're looking for as far as employment contracts.
The reason for it is because it's such a small field, the idea is to screen people in, not to screen people out and so once we can identify people that are strong candidates in the field, it's more about trying to nurture our relationship with particular people then dismiss people who might not meet X, Y, Z requirement.
I think the paradigm of recruiting is supply and demand and so I think of it very similar to AI.
Five years ago, AI was a very small field and now Microsoft has done things like implement the AI school in trying to broaden the people that are involved in the field. Quantum is going to I think take the same trajectory as followers growth and the people in it but yes, current state it's very opposite to how you might think of traditional recruiting work.
Jason Howard: So, Dave obviously we've talked a lot about education and past and histories and things like that. So, looking back on your education and career, what prepared you for the job that you have today? Did you see this coming a year, excuse me, even like a decade ago? Like did you know that this is what you would be working on?
Dave Wecker: No. Not even close. I actually had a career before Microsoft as an International Business Consultant, that where I ran around the world working in developing countries, bringing computer science there. When I came to Microsoft, I worked on all the little devices, handheld PC, Pocket PC, auto PC, I was the architect for all of those and development manager. Worked up to the Cloud, did a lot of work on the early cloud work page ranking, things like that efficiently. Along the way, the quantum team that was just beginning at that point didn't have any software tools.
It was all about the physics, it was all about the how do we make a device that will do what we want? Again, Microsoft has a very unique approach called topological quantum computing, which is a whole separate subject, but there was nothing to support what we were doing, so I wrote a simulator and that became what was known as Liquid that we shipped a number of years ago and was the predecessor to all the Q# work that you're seeing now and the QDK.
But it was one of those things where all the software had been done, had been done by grad students as part of their doctorate.
What that means is they just did enough to get the doctorate and things that didn't work and things that were just cobbled together were left that way. There was no professional effort.
The Liquid was the first example of what happens, we do professional computer science and apply it to the problem of quantum computing. And it was something that led us scale to approach some of the problems that we'll be able to solve on a real quantum computer someday.
So, my background was more of a generic type of thing, I've had all sorts of jobs over time, I used to say, “I just can't keep a job,” but it's also the case that my position as architect, architect is not a job you really train for. It something that along the way you've picked up the experience. You've gotten to the point where you understand how to build things that are going to last as opposed to, "I'm going to program something to a set of specs, get it done, get it out the door" which is more tactical, you have to get that done.
Architects are more looking at, "I want to build a framework that even if we only implement a little of it, leads to something that lasts for five years, ten years and beyond.” This is why things like internet protocols and the web standards and so forth are things that are architected, because they have to last for a long time.
Well, when you build a system this complex, you have to architect it, it has to be something that, you kind of have changed things but along the way you want to make sure much of it survives over time. I think it's more of an experience type of thing. You get as much training in many areas as you can, educationally, but you also get as much practical experience along the way. As I said, my backgrounds are in hardware, software business in all different areas and then I can pull it all together and use it in this position. So, this for me is the dream job. It's perfect for me.
Jason Howard: So, knowing how broad and diverse your background is, are there any specific skills that you found through your past and your jobs and the changes, the not keeping a job experience that you've had, are there any particular skills that have served you well but they are not to just served you well but it turns out that you may not have expected it but were actually super important to where you are right now.
Dave Wecker: Listening. Learning. In fact, my previous boss Burton Smith who kind of started a lot of this program, used to only ask me two questions on my review and the two questions were, "What have you learned, and are you having fun?" Because if you enjoy what you're doing and you keep learning and growing, the rest will come naturally. Those are the main skills. I really think I spend a lot of time getting educated, and there's always more, and applying it where I can and then training others.
A lot of my job is imparting this information. Quantum is something that doesn't come naturally to a lot of people. I think Feynman said it doesn't come naturally to anyone.
So, it's one of those things where I spend a lot of time just linking up parts of the program and saying, "You should talk to you, because the two of you are actually working on things that intersect even though they don't look like it. And you really should talk to each other." That's a lot of my job.
Jason Howard: I find it utterly fascinating. Like you have this awesome job and I'm just like, "I didn't even know we were working on this stuff." Until Satya showed some of this stuff on stage, I was like, "Wait a minute, what are we doing?" I always use my mom as an example because she's just she's my mom, she's old school.
This is not anything that would ever cross her plate. It's not something she'd ever seek it on the internet. She would never do research on it. Every time we do these and I do the webcasts that we do, she learns a little something and then we end up having phone call she's like, "Okay. So, I didn't understand this, tell me about it."
So, it's like this whole trickle-down effect. I will never be as smart as you. I will never do a tenth of the things that you've done obviously, but you talking and having this conversation with me, gives me a few little nuggets of knowledge and then I'll go pass those to my mom and she can go talk to other people. I think just getting people interested in this, is enough to help get the wave going.
Dave Wecker: I spend a lot of time at parties with my wife's friends explaining quantum. I get a question almost at every party where, “I heard this, and I saw this in the press, what does it mean?” Most of all of it is explainable. None of it is really stuff that's over anyone's head. It's just you're not familiar with it. You haven't heard it.
If anyone's interested also on cloudblogs.microsoft.com/quantum, we have a whole bunch of information for everybody including, there's a talk by me that's an hour-long talk on the overview of quantum and how Microsoft's effort is different and how it fits in with the rest.
But we've been doing quantum since the year 2000 and we created Station Q in 2006, it's just nobody knew it. So, we've been at this for a long time.
Tyler Roush: Not to overstate it but that Liquid system that Dave mentioned, I think it was one of two compiler systems in the entire industry at one point, not too long ago?
Jason Howard: My goodness.
Tyler Roush: And this year, it was up to six. So, even over the last couple of years, it has grown significantly.
Jason Howard: Wow. So, stepping back up a level, right? Obviously, in the technological sphere as a whole, we're in a period where technology is advancing at a much more rapid pace, which has happened since computing was invented. We're kind of always on this massive upward trajectory where something new is always around the corner.
Do either of you have any advice for new grads, people coming in right out of high school, or coming out of college who may not have known that this was a thing. It may have caught their interest if they had known about it beforehand. Any advice for those folks, or even some seasoned pros out there who are wondering how they can keep up. Obviously, you mentioned the Microsoft.com link earlier. If there's folks who want to decide what direction they should pursue their career, if this is something they’re interested in.
We talked about job roles versus candidates and things like that, but there's somebody out there who would be a good fit in this, but they don't know it yet. How do you get your foot in the door?
Dave Wecker: Well the easiest, using the Quantum Development Kit. Download it, and start writing some code, look at the examples. There's a large set of documentation with samples, with libraries, with all the things you need to get started.
Earlier this month there was a contest for people to just come in and write Q# code and compete in, and we're running events all the time. It's something that is free it's easy.
If you write software, you'll find in five minutes you can be writing a quantum algorithm. It's not that hard to get the basics and to get started. Details are going take a little while, but everything does, that's why it needed a new language among other things, but it's also something that you can do easily on your own. You can get started, there's more and more college programs starting now for training.
If you're coming from the computer science side, that's happening. Coming from the physics side, quantum information is becoming more and more of a thing that's being trained.
University of Washington has a class where they do quantum information now, and there's various places that you can move on to the computer science side from the physics.
So you can go both directions and it's more just explore and see what's available.
Tyler Roush: I think the advice I'd give to any candidate is to continue to think of your career as retooling into the current world. For computer science in the case of quantum, one of the interesting conversations that I had with my boss recently was, when he had started his career in recruiting, Webmaster was the most sought after profession, because the internet had just come out everybody was going to be a Webmaster. And so you think about how computing is changed to more distributed systems, Cloud oriented environment, AI, which is prevailing more and more today, and then the future in quantum computing just to continue to think about the relevance of programming in these modern systems.
The way that I understand quantum computing too, there is going to be a particular market for it, and so it's not going to overhaul all of computing systems but there'll be a certain application for it.
Dave Wecker: It's worth mentioning that quantum computing is a different mindset when you write programs. There are certain things that don't work, and certain things that do work compared to classical that you're used to.
You can't make temporary variables, you can't make a temporary that you copy something into, do work, and throw it away, it's actually impossible on a quantum algorithm. Most of the algorithms you write have to be able to run forwards and backwards. You have to be able to start from a state, run your algorithm, and then run the whole algorithm backwards and get back to where you started. This is very different than classical.
So, the mindset is different. If you love solving puzzles, it's a great area because every program is a puzzle solution of how do I figure this out, how do I make it do something I want it to do within the restrictions. So, it is something that takes practice, that takes a mind shift.
But also we found that a lot of the things we do in quantum because they're so different, let us solve things on the classical side we couldn't before. Because you've now thought about the problem from a different way, and we have a whole effort on Azure in quantum inspired algorithms, things we've learned in quantum that we've brought back say for machine learning that we now do Quantum inspired algorithms for machine learning on classical machines. So it also will help classical programmers to have this idea of how you think differently for quantum, and then applying that back to classical.
Jason Howard: Well I've got to say this has been a completely fascinating conversation for me, I mean even just in this short little back and forth between us. I've learned a ton. There's way more to come in this field as you continue to make new hardware, and make new software, and apply it to the problems that actually exist out in the world. So, as we wrap up here, are there any parting words or tidbits of advice you'd like to share with our listeners?
Dave Wecker: I think that quantum gives us an opportunity. It's a paradigm shift. It gives us a different way to think about problems, different way to solve problems. And it's something that is new. We've been computing with the same types of bits and numbers for thousands of years and this is a different way to do it.
One area we've left out of all this is math.on't forget about this if you're a Math major also, because a lot of the things are fundamental things in math, especially in topology and various other areas that besides physics and computer science, there's another way to come at this. And we have a large group of theoreticians in Santa Barbara at Microsoft working in this area as well. This is the home of Station Q, where it started, so this actually started as a mathematical idea, and moved out into the rest of it.
Alexei Kitaev is probably the father of topological quantum computing, and has worked with us from the beginning on this. Michael Friedman who heads Station Q in Santa Barbara, is a Fields Medalist. In math, that's the equivalent of the Nobel Prize. He's the only one working in industry, and has been with Microsoft since around 2000, working on this problem and trying to turn it into a reality. So, these are some of the best people in the world.
When I said that at the beginning, I really meant it I mean these are the Nobel Prize level people that are solving the problem, and we get to work with them every day here. So, I think it's a great job and a great place to be.
Tyler Roush: I'm just impressed with the leap that quantum computing will take--no pun intended--but when I first started with this group, I was thinking of Moore's Law and the trajectory that computing power has taken every two years. Moore's Law it doubles, and we get more computing power now. We can do more on our phone than we could 30 years ago with a computer.
So to think about quantum computing, it is exponentially faster to the point of almost being unexplainably faster, and I think the power that will come along with that will create an entirely new job market for candidates. It'll be part of the computer scientists’ world to figure out how that new world develops, and if you are interested in looking for a job, Quantum Jobs at Microsoft.com is a great place to reach me.
Jason Howard: Awesome.
Dave Wecker: I'll give one example of that exponential that we like to just let roll off our tongues. Two hundred and fifty qubits is enough to hold more information than there are particles in the universe.
Jason Howard: That's difficult just a fathom, as a statement much less the actual mathematical, volume and size that's inherent in what you just said.
That's right, so when we say exponential, it really means completely different. There are things that just cannot be done in any other computing paradigm that we have that could be done here. This is why I get up in the morning and go in and work on it every day.
Jason Howard: Well I gotta say, I really appreciate both of you popping into the studio today. It's been completely my pleasure and hopefully the listeners have enjoyed the conversation as well. Thank you for taking the time. Thank you for being in the studio today. Really appreciate it.
Dave Wecker: My pleasure
Tyler Roush: Thank you.
Jason Howard: Up next, the Windows Insider Program’s Tyler Ahn gets the inside scoop on what it takes to land a coveted internship at Microsoft--and, how to turn that internship into a job offer. Here’s Tyler.
Tyler Ahn: Hello insiders, our next guest in the studio today is here to talk about his experience as a Microsoft intern, and how he was able to land a full-time job offer from Microsoft.
Raymond, welcome to the show.
Raymond Ononiwu: Hey Tyler. Thank you, thank you for having me.
Tyler Ahn: Could you introduce yourself to our listeners and share a few words on your background and what you do here at Microsoft.
Raymond Ononiwu: My name is Raymond Uchenna Ononiwu, and I was born and raised in Lagos Nigeria. The unique thing about Lagos is that it teaches you to dream. Most people who have been to Lagos have interactive with Lagosians know we have this dogged determination to succeed at things. At the age of 17, I moved across the world to go to college. I started out doing Civil Engineering at Michigan Tech and three years into Civil Engineering program, I switched to Computer Science. Everyone thought I was crazy, but I figured it was a feature. It was necessary for me to do. I'm currently a software engineer for the CoreOS and Intelligent Edge here at Microsoft.
Tyler Ahn: What prompted you to switch from Civil Engineering to Software Engineering?
Raymond Ononiwu: It was actually one of those things that happened by chance. I didn't get to use a computer till I was 15 and on the long list of things I thought I could do, working with computers and computer science was not one of them. I remember a friend of mine at some point handed me, this was interesting, he said to me, he said you'd be really good at this computer thing and I just waved it off as though we're nothing and he handed me a Cisco switch and a book about routing and it actually had never occurred to me how an email gets from one end to another.
After reading the book and playing around with the switch, something just changed. I became fascinated with how information moves, digital information moves from one point to another, and that spurred the change to figure out what career path I had to take or what I had to learn at school in order to make this a career path and that's what spurred the change to Computer Science.
Tyler Ahn: That's so cool. Well, so what I heard was that you were once upon a time an intern here and internships are incredibly competitive these days especially with technology companies like Microsoft. Can you share what your experience was like applying for that internship.
Raymond Ononiwu: Well, it was quite an interesting one. I remember seeing a Microsoft recruiting booth on campus. It was during career fair I think, and I dropped off my resume, I didn't think much about it. I didn't actually think I had the opportunity. I didn't see a computer ‘till I was 15, and working with computers wasn't on my list of things to do.
When I got an email regarding the interview, I was quite elated because I didn't think I'd make it that far, and I remember my on-campus interview was with a guy named Jim Pemburton, and I spent about 35 minutes with Jim and I decided I wanted to work at Microsoft. He was excited and he had a lot of knowledge that he was willing to share which was quite frankly what I looked for in a company.
Past that point, we got invited, I got called for an on-campus interview which was, it was a little bit of a mix between, I would say being at the Grammy's and rigorous day, five 45-minute interviews to test our problem solving and design skills. I got my offer the same day at about midnight and I spent another 30 to 45 minutes convincing my parents that it was the same Microsoft that makes windows.
So it was quite an interesting process.
Tyler Ahn: That is so awesome. So what I guess you don't know really why they called you out of the stack of resumes, but in your view, what do you think helped you successfully land the internship? What made you stand out as a candidate?
Raymond Ononiwu: I think through the course of the interviews, showing that I was a learner was very important. I asked for a lot of feedback and I was more, the interview quite frankly went both ways. I was being interviewed and the entire time, I was actually interviewing the people who I was talking to. I think the ability to show that you can embrace the future was quite important.
One of the key things I believe helped me make it through that interview was the fact that I had switched majors in my third year and decided you know what, this is what the future's going to be and I need to go down that direction. It was quite a bold move and I think that stood out through the course of the interview.
Tyler Ahn: The ability to embrace the future.
Raymond Ononiwu: Yes.
Tyler Ahn: And the unknown.
Raymond Ononiwu: And the unknown, yeah.
Tyler Ahn: Well looking back, what was your internship experience like? What was most valuable? What skills did you gain in the months that you were here?
Raymond Ononiwu: Let's see. So, the internship itself was quite fun because I had a few other people from my school who were interning at the same time. One of the things I realized quite early was that as an intern, you have a golden key that unlocks doors to different opportunities.
You have a company that has people who are experts in their field, and you can always reach out and say, hey, can I have lunch and pick your brain and just soak up as much knowledge as you can. I think that was the biggest takeaway for me. The caliber of people that I got to work with and meet was quite amazing.
Tyler Ahn:What was the best piece of advice that you received during your days here as an intern? Or maybe even as a career Microsofty?
Raymond Ononiwu: I think the best advice I received as an intern was from Felicia Guitti, I believe. She is the GM of marketing, worldwide marketing, she was at the time, and I remember having lunch with her and she said to me, you decide what comes off of this process. Do a lot of the hard work and when you have to engage with people be very direct about what it is you need them to do for you or what you can do for them.
It's important to know those things in any kind of engagement or interaction with people at the company. Don't waste people's time, but also always have value to offer in any situation.
Tyler Ahn: How have you used that piece of advice?
Raymond Ononiwu: Oh, interestingly, I'm more in the social end of things. I tend to chit chat a lot with people but I will say, through the course of my time here at Microsoft, being able to articulate what it is that I can do for people has been important. You tend to build a brand over time, right?
People start to figure out what they know you for, and for me it turned out to be network, and I seem to know practically everyone. It's gotten to a point where even when new people show up at the company, especially who are Africans, the first email is reach out to Raymond, he'll figure out who you need to meet or what you need to do. So, I think it's connecting people that has become sort of my brand here at the company.
Tyler Ahn: Fantastic. So, we know that many interns are dreaming of working full time for Microsoft and with so many bright candidates only few actually realize that dream. What in your view helped you land that job offer after the internship was over?
Raymond Ononiwu: The people you work with make a huge difference. So when you look at yourself as a candidate for employment anywhere, you need to think about why you would hire yourself and be very honest and critical about it. Are you willing to learn quickly? Can you share your knowledge with other people?
I tend to think of it as coming prepared with the right tools but still leave enough space in your toolbox for new things. I think one of the interesting things I saw when I started here was that everyone who worked here either as an engineer and any other role had life experience, they had other things in their lives that they did.
So, the crazy things that I do in my life, be it racing or playing soccer or playing music, still mattered. Those things are equally as important because, in order for us to build great products we need to experience life first and figure out how to improve life using engineering. So, I think that was quite important as well.
Tyler Ahn: Learning how to crash the Oscars perhaps?
Raymond Ononiwu: Yes, that too.
Tyler Ahn: So any other wise and sage career advice you can offer new grads dreaming about working here at Microsoft?
Raymond Ononiwu: First off, join the Insider Program. That's important.
Tyler Ahn: Thanks for that plug.
Raymond Ononiwu: Form a habit of learning, not just the easy things but the difficult things as well. Learn to create clarity. Making complicated things simple is not an easy feat. So you have to practice a lot to be good at it. Practice everything. Be curious and don't just practice the engineering bit encoding, look into other aspects of life? How does your brain work? What is cancer? What makes it such a deadly disease, right?
Understanding those things that seem to be outliers usually are the key to solving a lot of problems. When you get there just enjoy it, time flies. It passes quickly, just enjoy it as much as you can.
Tyler Ahn: Raymond, that wasn't just great career advice, that was excellent life advice as well.
Thank you so much for joining us today, and to all the new grads out there, we wish you the best on your career journey and thank you for listening today insiders.
Jason Howard: That’s a wrap for Episode 17. If you enjoyed this episode, don’t forget to subscribe on your favorite podcast app. You can also find all of our previous episodes on the Windows Insider website: Insider.windows.com. Thanks again for listening, and until next time!
NARRATION: The Windows Insider Podcast is produced by Microsoft Production Studios and the Windows Insider team, which includes Tyler Ahn -- that's me -- Michelle Paison, Ande Harwood, and Kristie Wang.
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Thanks, as always, to our program's co-founders, Dona Sarkar and Jeremiah Marble. Join us next month for another fascinating discussion from the perspectives of Windows Insiders.