Principal Machine Learning Engineer

Microsoft • Redmond, WA

53d

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees