What you'd actually do

Design, implement, and evaluate novel methodologies for scientific discovery through artificial intelligence, non-exhaustively including techniques around post-training, inference-time optimization, interpretability, and experimental design.

Leverage a background in state-of-the-art techniques to post-train and fine-tune for application-specific scenarios.

Develop approaches for inference-time optimization of interaction patterns with deep learning models, e.g., context optimization, intelligent sampling, etc.

participate in robust, repeatable team-based technical research and be effective communicators.

Skills

Required

Doctorate in relevant field or equivalent experience
Design, implement, and evaluate novel methodologies for scientific discovery through artificial intelligence
Deep Learning Training Methods
System Optimization

Nice to have

Experience creating and using generative AI or other ML techniques in the life sciences.
Experience with pre-, mid-, and/or post-training deep learning models.
Experience innovating software, systems, or workflows that leverage generative AI-based systems to solve real-world problems in the life sciences.
Experience creating robust, repeatable technical research artifacts as part of an interdisciplinary team.
Experience publishing academic papers as a lead author or essential contributor.

Overview

Health Futures is a mission-focused organization within Microsoft Research, working at the forefront of artificial intelligence, healthcare, and life sciences research. We are a global and diverse team of engineers, scientists and domain experts who are working on expanding the technological frontier of health and life sciences through deep research. 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 between all three. Our mission is to empower every person on the planet to live a healthier future.

We are looking for a **Senior Researcher - Machine Learning - Microsoft Research **to help us advance the ways artificial intelligence can accelerate and advance discovery in biomedicine and the life sciences. This role is ideal for a candidate with intellectual curiosity who wants to craft a research agenda, articulate it clearly to team members with a diverse set of backgrounds, and execute on it as a member of that research team. Successful applicants will bring deep expertise about AI and will be passionate about making new discoveries in health and the life sciences

#Research #MSRR

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

Design, implement, and evaluate novel methodologies for scientific discovery through artificial intelligence, non-exhaustively including techniques around post-training, inference-time optimization, interpretability, and experimental design.
Deep Learning Training Methods: Leverage a background in state-of-the-art techniques to post-train and fine-tune for application-specific scenarios.
System Optimization: Develop approaches for inference-time optimization of interaction patterns with deep learning models, e.g., context optimization, intelligent sampling, etc.
In addition to these specific technical areas, candidates will be required to participate in robust, repeatable team-based technical research and be effective communicators.

Qualifications

Required Qualifications

Doctorate in relevant field
- OR Master's Degree in relevant field AND 3+ years related research experience
- OR Bachelor's Degree in relevant field AND 4+ years related research experience
- OR equivalent experience.

Preferred Qualifications

Experience creating and using generative AI or other ML techniques in the life sciences.
Experience with pre-, mid-, and/or post-training deep learning models.
Experience innovating software, systems, or workflows that leverage generative AI-based systems to solve real-world problems in the life sciences. This includes techniques like context engineering, prompt optimization, and optimization of test-time compute.
Experience creating robust, repeatable technical research artifacts as part of an interdisciplinary team.
Experience publishing academic papers as a lead author or essential contributor.

Research Sciences 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.**