We are seeking a Senior Machine Learning Engineer to drive the design and training of generative models in close collaboration with ML researchers, software engineers, and domain experts. This is a hands-on technical role focused on advancing state-of-the-art model capabilities across a variety of domains and modalities.

You’ll have the opportunity to tackle everything from model training to data and evaluation pipelines. Your work will span the full spectrum of model development – training and optimizing models on the latest hardware, devising new ways to assess their capabilities, and evolving data and training workflows to maximize model utility.

Microsoft Research New England is comprised of full-time researchers, postdocs, data scientists, engineers, and program managers working in machine learning, statistics, healthcare, computational biology, theoretical computer science, algorithmic game theory, economics, among other disciplines. The lab is highly collaborative and interdisciplinary and is actively engaged with the local academic and tech communities.

We are committed to building an inclusive, diverse, and pluralistic research environment. In keeping with this, Microsoft Research New England is a place where all are able to do their very best work.

• Lead the training of large language and multimodal models, including developing training workflows as well as managing, optimizing, and debugging such runs.
• Develop data and evaluation pipelines designed to maximize the performance of trained models.
• Mentor and provide technical leadership across the team and org in your area(s) of expertise.
• Explore and advise on strategic direction and technical approaches for projects across the team.
• Collaborate with researchers, domain experts, and cross-disciplinary teams to ensure our techniques translate the latest research into impactful solutions.

Required Qualifications:

• Bachelors or Masters in Computer Science or related technical discipline and 3+ years of technical engineering experience in ML-related work OR a Doctorate in Computer Science or related technical discipline.

Preferred Qualifications:

• Applied technical experience in one of: distributed training of deep learning models, data pipelines for model training, or evaluation workflows for assessment of model capabilities.
• Deep experience with PyTorch or Jax.
• Experience with designing, optimizing, and monitoring generative modeling training workflows.
• Familiarity with profiling training and/or inference code, identifying performance bottlenecks, and mitigating them.
• Comfort with one or more of: optimizing data mixes, midtraining, post-training, model merging, or model distillation.
• Effective communication skills with the ability to present complex technical concepts to a broad audience

#Research

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

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, read more about requesting accommodations.