Cambridge Residency Programme: AI Researcher

at  Microsoft

For our Microsoft Research Cambridge (UK) location, we are seeking highly motivated AI Resident candidates in the area of Deep Learning and Artificial Intelligence (AI) agents with applications in Gaming.
The successful applicant will work alongside prominent researchers and experienced engineers on driving machine learning technology that leverage unique data sets and applications in gaming.
This will include developing new insights in areas such as imitation learning, reinforcement learning, contrastive learning, generalization, and human-AI collaboration, and to help develop technology that can be used to positively impact billions of gamers. This is an exceptional opportunity for a recent graduate or an early career researcher to join a collaborative and interdisciplinary Agile team, and generate high impact in the form of product transfers and publications. We have an ambitious agenda, and we are passionate about learning and solving problems together. Working with the world’s best researchers and research engineers at Microsoft Research, this role gives you the opportunity to seek innovative solutions to the world’s toughest challenges and improving the lives of people everywhere.
When submitting your application, include your CV with a list of publications as an attachment. You may also include links to examples of your published work.

REQUIRED/MINIMUM QUALIFICATIONS

• Master’s Degree in Artificial Intelligence, Machine Learning, Computer Science, or a related area AND at least one year of research experience.
• Research experience in deep learning, including understanding state-of-the-art model architectures, data pipelines, and methods of evaluation.
• Research experience in at least one of the following or related areas: imitation learning, reinforcement learning, generalization, contrastive learning, model compression/distillation.
• Hands-on knowledge of deep-learning frameworks, including knowledge of how to implement, train, and validate deep learning models.
• Experience publishing academic papers as a lead author or essential contributor.

PREFERRED/ADDITIONAL QUALIFICATIONS

• Doctorate in Artificial Intelligence, Machine Learning, Computer Science, or a related area, OR equivalent experience.
  Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

• As a part of the team, you will be working with world-class researchers, engineers, UX researchers, and design experts, to generate novel ideas and opportunities to showcase novel machine learning techniques in video games, with the goal to inform or unlock future applications in Gaming.
• Collaborate to implement and evaluate new approaches, both conceptual and practical, within existing or new collaborations within the group and with others.
• Contribute to deliver the team’s goals by supporting every task, from generating novel ideas, to solving engineering challenges, to running experiments, to building infrastructure, to leading meetings, to doing demonstrations. We leverage everyone’s skills, but we are not defined by job titles!
• Share knowledge and learn from others, participating in design decisions, presenting your ideas, doing pair programming, reviewing code, etc.
• Help to continuously improve our ways of working and the quality of our work, giving constructive feedback, understanding other points of view, suggesting new processes, etc.
• Distil insights into effective communications, such as research papers and presentations, or other forms of communications (for example blog posts) to reach technical and general audiences.