(Senior) Scientist, Machine Learning

Responsibilities

• Develop and iterate on ML models for complex measurement data, from representation design through validation
• Design objectives and architectures that respect known constraints, symmetries, or latent structure in the data
• Explore and compare modeling strategies, balancing strong baselines with more experimental approaches when appropriate
• Investigate model behavior and failure modes to improve robustness and interpretability
• Collaborate closely with experimental and technical teammates to align modeling with data generation
• Contribute to shaping the long-term ML strategy and technical direction of a new venture

Requirements

• You likely:
• Think algorithmically and reason from underlying structure
• Are comfortable adapting or extending model architectures when needed
• Have built and debugged meaningful ML systems or research prototypes
• Enjoy operating in dynamic, early-stage environments
• Read papers, build prototypes to test ideas, and translate concepts into working systems
• What matters most is your ability to reason across data, models, and the systems they represent.
• Technical Background
• Required
• Strong hands-on experience building and training modern ML models
• Fluency in Python and at least one major ML framework (e.g., PyTorch or equivalent)
• Experience working with real-world or experimentally generated data
• Ability to design, run, and interpret ML experiments
• Comfort working in practical development environments (e.g., cloud infrastructure, experiment tracking, reproducible workflows)
• Helpful
• Experience with inverse problems, latent-variable inference, or structured generative modeling (e.g., diffusion or flow-based methods)
• Familiarity with geometric or symmetry-aware architectures
• Experience incorporating physical or structural constraints into learning systems
• Experience working with time-series or high-dimensional signal data
• Exposure to biology, chemistry, physics, or related sciences
• ABOUT FLAGSHIP PIONEERING
• At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.
• We are an equal opportunity employer . All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
• Recruitment & Staffing Agencies : Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than

Benefits

Additional Information

Build Models Where None Exist Yet. At Flagship Pioneering, we create companies from first principles. Within Flagship Labs, small founding teams define new technical theses, test them rapidly, and build ventures around breakthrough ideas. We are forming a machine learning team inside a newly launched venture, Flagship Labs 120. Our work focuses on extracting latent structure from information-rich measurements of complex physical systems-often requiring mechanism-informed modeling, thoughtful inductive bias design, and principled approaches to inverse problems. This is a zero-to-one role focused on modeling innovation rather than routine optimization. You'll design, prototype, test, and refine new approaches that help define the technical foundation of a platform from day one.

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