Staff Machine Learning Research Engineer - Foundational Models in Biology
Location: Cambridge, MA (Onsite, 5 days per week)
Compensation: $200K–$300K base + equity
About the Company
Our client is a pioneering biotechnology company at the intersection of machine learning and stem cell biology. Backed by top-tier investors with over $47M raised at Series A, they are redefining how human biology is modelled and understood by applying large-scale AI techniques to biological data.
The Role
The Staff Machine Learning Research Engineer will take a lead role in developing and training large-scale foundational models that bridge computational biology and modern AI. You’ll design, train, and optimize transformers, diffusion models, and other large-scale architectures, leveraging multi-GPU and distributed training setups to push the limits of what’s possible in modelling biological systems.
Key Responsibilities
- Design, train, and scale large foundational ML models (transformers, diffusion, etc.) on massive biological datasets.
- Collaborate closely with computational biologists and software engineers on cross-disciplinary research.
- Lead experiments in single-cell data modeling, contributing to next-generation bio-foundation models.
- Optimize model architectures and training pipelines for performance and scalability across large compute clusters.
- Publish results and contribute to the broader ML and computational biology research community.
- Mentor junior engineers and help guide the technical direction of the team’s research efforts.
Qualifications
Required:
- 6+ years of hands-on machine learning experience (or an exceptional postdoctoral research background).
- Proven experience training large models (LLMs, diffusion, or comparable architectures)—not just applying them.
- Strong proficiency in Python, PyTorch, and/or TensorFlow.
- Demonstrated record of research excellence (publications in top ML conferences or equivalent experience).
- Experience leading or contributing to large-scale distributed training runs (multi-GPU, multi-node).
Preferred:
- Background in computational biology, genomics, or single-cell data analysis.
- PhD in Computer Science, Computational Biology, or a related field.
- Experience working cross-functionally with wet lab, data science, and engineering teams.
- Strong collaborative mindset with interest in future technical leadership opportunities.
Why Join
- Be part of a mission-driven team advancing regenerative medicine through AI.
- Work with cutting-edge foundational model architectures applied to real biological data.
- Collaborate with top-tier researchers and engineers in a highly interdisciplinary environment.
- Enjoy a startup culture with genuine scientific ambition - where ideas move quickly from concept to impact.
- Competitive compensation with meaningful equity and relocation support for top candidates.
If this role feels like a strong match for you, we’d love to hear from you.
