Senior Machine Learning Scientist, Model-Driven Optimisation at Generate:Biomedicines
Job Description
Generate:Biomedicines is hiring a Senior Machine Learning Scientist to build the ML methods and closed-loop systems that decide what the company designs, builds, tests and learns from next. The focus is its lab-in-the-loop protein optimisation platform: sequential decision-making, experimental design, property modelling and scalable design systems.
At a glance
- Team: Model-Driven Design
- Location: Somerville, Massachusetts (hybrid)
- Pay: Listed on the posting (from $192,000 a year)
- Apply: open until filled (re-checked 14 October 2026)
What you would do
- Develop new ML methods and systems for lab-in-the-loop protein optimisation
- Work on sequential decision-making, experimental design and property modelling
- Lead complex projects from problem framing to deployment and experimental impact
- Partner with protein designers, wet-lab scientists and engineers
Why this role matters
Every round of lab experiments is expensive, so choosing which proteins to make next is where machine learning can save the most time and money. Bayesian optimisation and active learning are the core tools, and this role applies them to real therapeutic programmes rather than benchmarks. Few roles let ML scientists see their choices turn into lab results so directly. That makes it a strong fit for Bayesian optimisation and active-learning researchers.
What Generate:Biomedicines is looking for
- Depth in probabilistic ML, Bayesian optimisation, active learning or related methods
- Engineering discipline to turn ideas into reliable systems
- Technical leadership as a hands-on contributor
Nice to have
- Experience with biological sequence or protein data
Pay and location
Generate lists a salary range on the posting; the lowest figure shown is $192,000 a year.
How to apply
Apply through the official Generate:Biomedicines job posting. Generate:Biomedicines’s posting does not give a closing date, so the role is open until filled; ResearchJobs.in will re-check this listing on 14 October 2026. Check the posting for location and work-authorisation details before you apply.
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Hiring institution: Generate:Biomedicines
Official advertisement: generatebiomedicines.com
How to prepare for this application
- Decision-making under uncertainty: show Bayesian optimisation or active learning work.
- Real experiments: projects where models chose lab experiments are ideal.
- Systems: reliable, deployed pipelines matter.
- Leadership: the role expects technical leadership.
About Generate:Biomedicines
Generate:Biomedicines uses machine learning to design new protein therapeutics, combining generative models with its own wet labs in tight design–build–test–learn cycles. It is based in Somerville and Andover, Massachusetts.
