Overview
For our Microsoft Research Cambridge location, we are seeking highly motivated candidates to work on multimodal generative AI systems for dynamic and interactive environments (e.g. gaming and creative media), as well as real-world workflows. Our work focuses on developing systems that model and adapt to evolving environments, capturing how user actions and context change over time to support continuous processes such as creation and collaboration.
Successful applicants will work alongside prominent researchers, engineers, and experts across machine learning, HCI and design; and drive deep research insights to support the development of novel AI systems, leveraging our unique datasets and multi-node GPU infrastructure. This work is grounded in close interdisciplinary collaboration, bringing together diverse perspectives to advance ambitious research goals.
Candidates may come from either a Machine Learning modelling-focused background (e.g. multimodal generative modelling, world models, sequential prediction) or a Machine Learning systems-focused background (e.g. agentic workflows, orchestration, tool-using systems, training and evaluation pipelines) and should be excited about connecting these perspectives.
This is an exceptional opportunity for a recent graduate or an early career researcher to join a collaborative and interdisciplinary 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 contribute to open research challenges in generative AI for interactive environments whilst broadening your area of expertise and continuing to grow into an established research leader.
When submitting your application, please include a list of publications in your CV. You may also include links to examples of your published work.
Location: Cambridge, UK-
Contract Length : 2 Years
Responsibilities
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As a part of the team, you will be working with world-class researchers, engineers and design experts, to create novel generative AI models and capabilities that support creative processes. .
- Collaborate to implement and evaluate new approaches, both conceptual and practical, within existing or new emerging cross-company collaborations.
- Contribute to the team’s goals by generating novel ideas, implementing prototypes, running experiments, utilizing multi-node GPU infrastructure, and rigorously evaluating all ideas with an open mindset.
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Design efficient experimentation workflows to accelerate research iteration across the team.
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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.
- Distill 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.
Qualifications
Required/Minimum Qualifications:
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Master’s or PhD degree in Artificial Intelligence, Computer Vision, Machine Learning, Natural Language Processing, or a related field, OR equivalent experience.
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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: Generative models (video and world models, diffusion, autoregressive models, controllability), multi-modal modelling, training and fine-tuning large multimodal models or AI systems for multi-step interaction, such as agentic workflows, orchestration, tool-using systems, memory, or adaptive workflows
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Hands-on knowledge of deep-learning frameworks, with strong software engineering practices and a commitment to writing clean, maintainable and well-tested code.
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Experience publishing academic papers and/or demonstrated impact through ML research tooling or open-source contributions.
Preferred/Additional Qualifications:
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Experience scaling deep learning workloads to maximise responsible utilization of multi-node GPU clusters.
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Experience designing or implementing AI workflows, such as automated training, evaluation, or experimentation pipelines
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Familiarity with game engines or creative AI tooling and/or experience applying AI in interactive settings
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
