Senior Machine Learning Engineer

Reposted 5 Days Ago
Be an Early Applicant
Cambridge, MA, USA
In-Office
120K-261K Annually
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Lead the training, optimization, scaling, and debugging of large language and multimodal generative models for scientific discovery. Develop efficient training workflows, identify performance bottlenecks, guide technical strategy, mentor engineers, and collaborate with researchers and domain experts to translate advanced machine learning research into impactful solutions.
Summary Generated by Built In
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:
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.

Skills Required

  • Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience in machine learning-related work, or equivalent experience.
  • Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience in machine learning-related work, or a Doctorate in Computer Science or a related technical field.
  • Hands-on technical experience with distributed training of large language or multimodal models, 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 or inference code, identifying performance bottlenecks, and mitigating them.
  • Experience refining data mixes, midtraining, post-training, data or model parallelism, optimizing training runs, or model distillation.
  • Demonstrated communication skills and ability to present complex technical concepts to broad audiences.

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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The Company
HQ: Redmond, WA
206,870 Employees
Year Founded: 1975

What We Do

At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.

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