Microsoft AI Residency Program

Microsoft AI Residency Program


The application period is now closed for 2019-2020.

Gain new AI skills and experience while tackling real-world challenges

In September 2018 we welcomed our first cohort of residents into the program and are excited about the future impact on the fields of AI and machine learning. While the first class of residents are currently here and learning new skills we are eager to meet our 2019/2020 class!

Through our Microsoft AI Residency program you will have the opportunity to work alongside prominent researchers and engineers in either Redmond, WA, or Cambridge, UK. You will build your skills and get hands-on experience working on practical AI and machine learning problems that help tackle some of society’s toughest challenges.

We are searching for a diverse range of researchers, engineers, and applied scientists with unique perspectives, including candidates who may not have a traditional background in AI, but who are passionate about working on AI technologies to solve real-world challenges.

In this year-long program, selected residents will:

  • Gain real-world, hands-on industry experience while working with Microsoft researchers, engineers, and product teams.
  • Learn how to develop and deploy AI techniques and solutions at scale across a range of areas such as healthcare, scientific discovery, productivity, and gaming.
  • Benefit from a rich program of training and mentorship.
  • Be part of a vibrant AI and machine learning community in Cambridge, UK, or Redmond, WA.
  • Receive competitive compensation and be encouraged to apply for a regular position at Microsoft at the end the residency program.

We look forward to working with candidates that can carry the work forward into the future.

Eligibility criteria

  • BSc, MSc, and PhD graduates with substantial coursework in, but not limited to: computer science, electrical engineering, data science, mathematics, physics, economics, human-computer interaction, and computational biology.
  • Experience developing in at least one high-level language such as Python or C/C++/C#.
  • Experience with machine learning techniques or deep learning frameworks is desirable.
  • Enthusiasm to move into the field is essential.
  • Ability to work in a highly collaborative and interdisciplinary environment.
  • Strong communication skills.


2018 – 19 residents have been identified, please check back in the Fall for details of the 2019-20 residency program.

What is Microsoft looking for in a candidate for the Microsoft AI Residency program?

The ideal candidate will have a passion for leveraging their expertise from computer science work and/or other technical fields to solve real-world challenges by applying artificial intelligence (AI). We are looking for candidates with substantial coursework in, but not limited to: computer science, electrical engineering, data science, mathematics, physics, economics, human-computer interaction, and computational biology. Experience developing in at least one high-level language such as Python or C/C++/C# or experience with machine learning techniques or deep learning frameworks is desirable.

I have been out of school for several years, am I still eligible?

Yes, we will consider people with various degrees and experiences.

How do I apply and what does the application timeline look like?

While we reserve the right to adjust the timeline below based on hiring needs of the company and program, we anticipate the following:

  • Application Period: November 5, 2018 – January 31, 2019
  • Interview Period: February – Mid-March, 2019
  • Notification of Admission: Late March – April, 2019

What documents do I need to prepare in order to apply?

You will need to prepare and upload a cover letter and curriculum vitae (CV) in one document. Please follow the detailed instructions when applying for each of the residencies at the Cambridge and Redmond Labs.

What makes a good cover letter?

A good cover letter for this program is inclusive of at least two things. The first; what do you want to get from the AI Residency? The second; it’s helpful if you give us a bit more detail on your most recent project work and your current passions. Some other tips are to give specific examples of key achievements in your academic or professional career and don’t repeat your resume.

What benefits will I receive during the program?

The resident program offers benefits designed to give you a world-class experience. You will receive competitive pay, custom AI training from top researchers and engineers and wonderful health and care benefits.

Where is the residency program based?

The program is based out of two labs; Redmond, Washington, USA, and Cambridge, United Kingdom.

Will Microsoft sponsor my work authorization?

Where required, Microsoft will support the immigration process for eligible applicants. We will determine the best available visa/work authorization option. For those seeking employment in the USA, please note that the H1-B is not an option as this is a fixed term role.

What can I expect at the completion of the residency program?

Residents will be encouraged to apply for a full time, relevant, position at Microsoft at the end of their residency.

Will I be able to publish my work as a resident?

Yes, Microsoft strongly encourages you to publish your work to top tier venues and conferences.

What does the support system look like?

As a resident, you will experience an open-door environment designed to encourage you to set up a meeting with anyone at Microsoft. We encourage you to explore all areas of Microsoft while here and network through the company as desired.

From a formal project side, you will be assigned to a mentor/project lead who will be available to you as you work through your professional growth and project milestones. Bottom line, we want you to feel supported while you are here with us!

Have questions not covered in the FAQs?

Feel free to send your questions to

Please note the alias above cannot assist you in writing a resume or advise on specific courses or experiences needed. You can refer to the job description and if you feel you meet the basic requirements, we encourage you to apply.

Resident Blog

Residents at Work

Interview with Anna-Lena Popkes, AI Resident

Anna-Lena Popkes, AI Resident

Anna-Lena Popkes, AI Resident

Tell us a bit about your background.

I got interested in AI quite late. I started studying cognitive science in my undergraduate degree and planned to focus on neuroscience and research in this field. Only in my last semester, I came across a machine learning lecture. Afterward, there was no way back. I became so fascinated by the idea of algorithms that can learn on their own that I decided to switch fields, although I had no previous experience with AI or computer science. So I started studying computer science in my graduate degree with a focus on machine learning. It wasn’t the most straightforward path but was definitely worth it! I love what I’m doing. Although I still have many things to learn that other students with a computer science or math background may already be familiar with, I believe that an interdisciplinary background can also be beneficial.

After finishing my graduate degree in Germany at the beginning of 2018, I went abroad for a deep learning internship at the Bosch Center for Artificial Intelligence in Palo Alto in the U.S. My time at Silicon Valley convinced me even more that I chose the right path.

What project are you currently working on?

I’m working on a project applying Bayesian Neural Networks in health care. I was fortunate to be assigned to this project as it was my top choice. I had never looked at the field of Bayesian Learning before, so my AI resident partner and I had to do a lot of reading in the beginning. Now I like the project so much that I could continue working on it for the rest of the residency! Of course, the application in health care makes the project even more exciting and motivates us to achieve good results. In case the project succeeds, its results can be deployed in practice and have an actual impact on the wellbeing of patients.

Tell us about your team environment. What do you enjoy about collaborating with your small team and the larger MSR lab?

At the beginning of the residency, each resident was assigned to a specific project, together with another AI resident. We got matched up such that we have different skills and can learn from each other. That was great! My partner has been incredibly helpful – I don’t know what I would do without her. In addition to an AI resident partner, our project has an engineering supervisor and a machine learning/research supervisor. We also have two other researchers on our team who have been working on Bayesian Neural Networks for years. We meet with the entire team once a week to discuss our current progress, results, etc. We also have lunch together as a team once a week.

Apart from the project team, there is a lot of collaboration among the residents and MSRC in general. The residents help each other whenever possible. Other researchers and engineers in the lab are also happy to help when their expertise is needed, ensuring we get the best possible support.

How have you been designing your ongoing educational opportunities while in the residency?

Many lectures and other events are always happening at Microsoft Research Cambridge providing plenty of opportunities to learn. We also have an AI residency lecture about once a week. These lectures are intended to teach us essential skills like probability theory, etc. We are also allowed to spend some time during the week on learning new things. However, this is a skill I’m still cultivating. I can get so absorbed by our project that I find it difficult to stop working and look at a different topic.

Walk us through a day in the life of a resident.

During my day at work, I am usually coding or discussing new ideas or problems with my AI resident partner. We sit next to each other so it’s easy to talk in case a problem occurs. We often split tasks and review each others code afterwards. Around noon most of the residents have lunch together and then congregate around the ping-pong table. During the afternoon I sometimes attend talks or lectures I am interested in or one of the gym classes. When stuck on a coding challenge this can be quite helpful! Every two weeks we have a one-on-one meeting with the AI residency coordinator. During this time we can talk about anything that we feel is important, including problems or worries. I must say that the support system within Microsoft has been fantastic. There is always someone around to talk or help, no matter what the issue might be.

My Path to AI Residency

Interview with Blake Elias, AI Resident

Blake Elias, AI Resident

Blake Elias, AI Resident

Tell us a bit about your background.

I recently completed the Bachelor of Science and Master of Engineering degrees in electrical engineering and computer science at the Massachusetts Institute of Technology (MIT). I always wanted to understand and augment human intelligence. As a result, I took symbolic AI courses, like Professor Patrick Winston’s “The Human Intelligence Enterprise” and Professor Gerald Sussman’s “Adventures in Advanced Symbolic Programming,” and read books like Marvin Minsky’s Society of Mind, which were absolutely inspirational.

Because I also wanted to take advantage of MIT’s other unique opportunities outside computer science, I took classes like “Biological Circuit Engineering Laboratory” with Ron Weiss and Tim Lu, and “Principles of Neuroengineering” with Ed Boyden. These disciplines promise to help us understand and enhance the human experience as well. For my master’s thesis, I developed a platform for low-cost, high-throughput automated DNA assembly using robotic pin tools.

Before this, I was the first employee of IdeaFlow [CrunchBase], which is building a human-AI hybrid “shared brain” for organizations. I’ve also done research in the MIT Media Lab on augmented reality for enhanced learning and memory, and was a technical program management intern at Google.

How did you find out about the AI Residency?

I had heard about similar programs through a jobs mailing list at MIT, so I started investigating those. At one point I saw a forum post discussing AI residency programs and someone mentioned the [then] newly launched Microsoft Research AI residency.

What made you decide to apply?

I thought an AI residency program would be a good way to improve my skills and work on some awesome projects. I liked that there would be opportunities for my research to go into products and/or free software projects, with an eye towards human-AI collaboration and having an ethical impact on people and society.

I was specifically interested in Microsoft Research because of its Neural Program Synthesis and Deep Program Understanding projects. While the AI world has been moving towards machine learning, I see a lot of value in the older symbolic AI that I learned at MIT. I’ve been wanting to combine these two approaches and these projects seemed like a great domain for that.

Six weeks in, what are your initial thoughts on Microsoft and your experience?

Microsoft is a great place to do research. We have the full R&D pipeline, from basic theoretical research to applied end-user applications, and everything in between. It’s interesting to see this all under one roof.

My current project combines SAT solvers with neural networks, to teach computers how to write simple programs. This is a core problem that asks “how can we combine statistical and symbolic knowledge – pattern matching with reasoning – when neither is perfect on its own?” I think progress here can illuminate new approaches in many areas of AI.

Microsoft Research is doing a wide range of research in many areas of computer science, and there is an opportunity for AI researchers to collaborate with other areas (in my case, for example, program analysis and verification).

What do you want to get out of the residency?

I want to improve my skills designing deep neural networks and develop insight on how to combine machine learning with symbolic AI. I also hope to learn guiding principles for developing technology with moral impact and that truly makes our lives better – not just faster.

My Journey to the Microsoft Research AI Residency

Interview with Andi Peng, AI Resident

Andi Peng's Journey to the Microsoft Research AI Residency

Andi Peng, AI Resident

Tell us a bit about your background/education/experience?

In school, I’d always been a bit of an academic mutt—I graduated from Yale with a BS in cognitive science and a BA in global affairs/security studies. If you’re wondering as to how orbitofrontal cortices relate to military statecraft and grand strategy, rest assured knowing that I, too, am still trying to figure this out. However, as disparate as these two disciplines seem, I think a fundamental question lies at the core of both: how do decisions get made in the real world, especially when one is faced with risk and uncertainty?

At Yale, I had the chance to explore that question from both bottom-up and top-down perspectives. In my cognitive science classes, I learned how psychologists and neuroscientists study human decision-making at the individual level, and how to model those processes computationally. In my global affairs classes, I learned how large-scale institutions, such as states and militaries, apply different models of decision-making in implementing policy at the organizational level. Along the way, I had the chance to work with a variety of different organizations, ranging from NASA to the UN, all who sought to understand and apply these principles in ways that would ultimately contribute to the betterment of the world.

How did you find out about the AI Residency and why did you decide to apply?

For the nine months prior to the residency, I was working in Washington, DC (the other, albeit very different, Washington!) on federal science policy, both at the White House Office of Science and Technology Policy, and the National Institute of Standards and Technology. Before the White House, I was a security engineer at Facebook and saw how targeted disinformation and the malicious use of technology can quickly impact our society. Then at the White House, I saw just how difficult it is to fix organizational problems on such a large scale. It’s no secret that this has been a tumultuous time in American history, both due to unprecedented political upheaval and unforeseen challenges posed by the rise of technology. Thus, I knew that the place I wanted to be at needed to have both the technical expertise to push forward the fundamental science on these issues, but also have strong leadership and demonstrate a willingness to engage on the ethical and social side. When I heard about the Microsoft Research residency, which has both, I knew it would be a great fit.

What do you want to get out of your year-long residency? What are your goals?

In this upcoming year, I hope to further develop technical expertise in the realm of AI and also continue contributing to the social dialogue on the ethics and fairness issues that have arisen. For example, when we as researchers develop state-of-the-art facial recognition software, how much responsibility should we have in ensuring that it’s not used to deliberately target people in a discriminatory manner? Or even worse, accidentally target them? My goal for my research is to ask questions such as these, informed both by an understanding of these technologies and their applications, as well as by the social contexts that shape and are shaped by these technologies.

Six weeks in, what are your initial thoughts on Microsoft Research and your experience?

The past six weeks have blown the expectations I had out of the water. Microsoft Research is an incredible place to work, filled with brilliant and engaging mentors that are all deeply engaged in advancing state-of-the-art AI in a way that positively contributes to the world. The first two weeks began with various project teams pitching proposals to the residents, and then a mutual match-making process began. For me, it was clear from the onset that one project was the best fit for my interests. I will be spending most of this upcoming year working with Eric Horvitz, Ece Kamar, and Emre Kiciman on a human-AI collaborative decision-making project. The Adaptive Systems and Interaction research group has adopted me as one of their own and I feel the love and support of belonging to a close-knit group of researchers who are all working on similar questions. I’m excited to have another ten-plus months to roll up my sleeves and dive deeper into these issues while working here.