Job description

Overview We are seeking a Senior Machine Learning Engineer to design, train, and optimize generative models for multimodal scientific discovery. This is a hands-on technical role where you’ll work alongside a multi-disciplinary team of ML researchers, engineers, and domain experts to develop the methods and tools needed to accelerate the rate of discovery and further the frontier of human knowledge . There is no one-size-fits-all approach – advancing model capabilities requires investment throughout the training lifecycle, including method development, recipe refinement, scaling and throughput optimization, and model-harness co-design. In this role, you’ll contribute to these workstreams and leverage their learnings to drive scaled runs. 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. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities • Lead the training of large language and multimodal models, including developing, managing, and debugging training workflows • Scale and optimize training runs, identifying opportunities for efficiency gains and implementing them • Mentor and provide technical leadership across the team and organization 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. Qualifications Required Qualifications: • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience in ML-related work • OR equivalent experience. Preferred Qualifications: • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience in ML-related work • OR a Doctorate in Computer Science or related technical field. • Hands-on technical experience in one of: distributed training of large language / multimodal models (pretraining, midtraining, or post-training), optimizing training workflows, or model distillation • Deep experience with PyTorch or Jax. • Experience 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: refining data mixes, midtraining, post-training, data/model parallelism techniques, optimizing training runs, or model distillation. • Demonstrated 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 $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com 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.

Requirements

Must-haves

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, managing, and debugging training workflows
Scale and optimize training runs, identifying opportunities for efficiency gains and implementing them
Mentor and provide technical leadership across the team and organization 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.
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience in ML-related work • OR equivalent experience.
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience in ML-related work • OR a Doctorate in Computer Science or related technical field.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Nice-to-haves

Hands-on technical experience in one of: distributed training of large language / multimodal models (pretraining, midtraining, or post-training), optimizing training workflows, or model distillation
Deep experience with PyTorch or Jax.
Experience 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: refining data mixes, midtraining, post-training, data/model parallelism techniques, optimizing training runs, or model distillation.
Demonstrated communication skills with the ability to present complex technical concepts to a broad audience
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningml

Platform: eightfold
Effort: medium