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About the Role
Advance the capabilities of frontier vision-language models through reinforcement learning, helping models understand visual information, reason from visual evidence, and provide accurate responses to complex multimodal questions. This hands-on research and engineering role involves owning projects across the research loop, from identifying capability gaps to implementing better models, and collaborating with cross-functional teams.
Responsibilities
- Advance visual understanding and multimodal reasoning through reinforcement learning, translating capability gaps into concrete research hypotheses and measurable improvements.
- Develop targeted training tasks and data, including synthetic data, to address these gaps.
- Design and validate rewards, verifiers, rubrics, and model-based judges for both verifiable and open-ended visual tasks, detecting and mitigating reward hacking.
- Build evaluations and conduct controlled experiments, ablations, and detailed failure analysis.
- Collaborate with scaling, multimodal, data, and safety teams to integrate improvements while preserving broader model capabilities.
Requirements
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field and 4+ years of relevant research or engineering experience; OR master's degree in a related field and 2+ years of relevant experience; OR PhD in a related field.
- Experience developing, training, or evaluating deep learning models, with demonstrated depth in at least one of model post-training, reinforcement learning, or vision-language modeling.
- Ability to formulate hypotheses, design informative experiments, analyze results, and debug model or training behavior.
- Ability to take end-to-end ownership of technical projects and collaborate effectively across research and engineering disciplines.
- Proficient programming skills in Python and PyTorch (or similar).
Skills
- Reinforcement learning
- Vision-language modeling
- Deep learning
- Model post-training
- Python
- PyTorch
Location
- U.S.
Work Type
- Full-time
Experience Level
- 4+ years of relevant research or engineering experience with a Bachelor's degree
- 2+ years of relevant experience with a Master's degree
- PhD
- 8+ years of relevant research or engineering experience with a Bachelor's degree (Preferred)
- 6+ years of relevant research or engineering experience with a Master's degree (Preferred)
- 4+ years of relevant research or engineering experience with a PhD (Preferred)
Education Level
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field
- Master's degree in a related field
- PhD in a related field
Salary/Compensations
- USD $119,800 - $234,700 per year (Software Engineering IC4, U.S.)
- USD $160,200 - $261,000 per year (Software Engineering IC4, San Francisco Bay area and New York City metropolitan area)
- USD $142,800 - $274,800 per year (Software Engineering IC5, U.S.)
- USD $188,000 - $304,200 per year (Software Engineering IC5, San Francisco Bay area and New York City metropolitan area)
Benefits
- Certain roles may be eligible for benefits and other compensation.
About the Company
- Microsoft AI is looking for a Member of Technical Staff to advance the capabilities of frontier vision-language models through reinforcement learning. Within our Large Scale Reinforcement Learning team, you will help models better understand visual information, reason from visual evidence, and provide accurate, useful responses to complex multimodal questions.
- Our work spans visual perception and grounding, document and chart understanding, image-to-code generation, and spatial and physical reasoning from visual inputs. We aim to develop capabilities that generalize to unfamiliar problems and real-world use, rather than simply improving benchmark scores.
Equal Opportunity
- 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, read more about requesting accommodations.