Staff ML Researcher

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.