Principal Machine Learning Engineer

Posted 15 Days Ago
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Redmond, WA, USA
In-Office
143K-304K Annually
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Lead design, training, and deployment of large-scale generative ML models for health and life sciences. Define ML pipeline architecture, optimize distributed training and evaluation, ensure security/compliance, and mentor engineers while collaborating with researchers and domain experts.
Summary Generated by Built In
Overview

Health Futures is a Research and Incubation team working at the intersection of computer science, signal processing, machine learning, and biomedicine. We are a global and diverse team of engineers, scientists, and medical doctors who are working on next-generation Artificial Intelligence (AI) tools and methods for health and life sciences. We offer a unique and vibrant environment that features innovative academic research, enterprise software development, and real-world delivery, with close feedback loops and rapid iterations among all three, much like a lean startup. Our mission is to empower every person on the planet to live a healthier future.  

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (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 scientific domains and modalities. You’ll spend your time working across the stack from curriculum design, to debugging training runs, through developing new evaluation methods and high-performance inferencing – with a goal of improving all phases of our training process.
 
As part of Health Futures, 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. Beyond model training, you’ll participate in explorations of how these models can and should be used in the real world – and the systems required to successfully operate them.

At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.


Responsibilities
  • Lead the design and development of machine learning models and systems for health and life sciences applications, ensuring scalability and reliability.
  • Define technical strategy and architecture for ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
  • Collaborate with interdisciplinary teams (including scientists, researchers, and software engineers) to envision and develop AI-augmented scientific systems.
  • Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles.
  • Ensure security, privacy, and regulatory compliance across ML workflows and data handling.

Qualifications

Required Qualifications

  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.

Preferred Qualifications

  • Masters in Computer Science or related technical field AND 6+ years technical engineering experience including significant work in machine learning or applied AI
    • OR equivalent experience.
  • Proven track record of designing and deploying large-scale ML or MLops systems in research or product settings.
  • Hands-on experience with large-scale distributed training of ML models.
  • Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow).
  • Experience with one or more of: optimizing data mixes, mid-training, post-training, model merging, or model distillation.
  • Familiarity with security and compliance standards for enterprise and health data.
  • Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environment.

#Research #healthfutures #researchsystems


Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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 related technical field AND 6+ years technical engineering experience (or equivalent experience).
  • Proficiency coding in C++, C#, Java, JavaScript, or Python.
  • Master's in Computer Science or related field with 6+ years including significant ML or applied AI work (or equivalent experience).
  • Proven track record designing and deploying large-scale ML or MLOps systems in research or product settings.
  • Hands-on experience with large-scale distributed training of ML models.
  • Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow).
  • Experience with optimizing data mixes, mid-training and post-training techniques, model merging, or model distillation.
  • Familiarity with security and compliance standards for enterprise and health data.
  • Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environments.

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
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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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