Metric Bio is hiring: Machine Learning Engineer – Biological Foundation Models i
Metric Bio, boston, ma, United States
Machine Learning Engineer – Biological Foundation Models
Metric Bio has partnered with a venture-backed biotech at the intersection of AI and cell biology. This team is building foundation models on trillion-token scale biological datasets to reimagine how we create cell therapies.
This is a role for someone who doesn’t just apply existing methods but creates new ones; first-author researchers, system builders, and innovators who want their work to drive real therapeutic impact.
Responsibilities:
- Design and optimize foundation models for single-cell and multi-omics data, leveraging transformer and generative architectures.
- Build scalable distributed pipelines (multi-GPU training, trillion-token inference) to push biology into true foundation-scale.
- Collaborate closely with computational biologists and wet-lab teams , ensuring models produce interpretable, biologically meaningful outputs.
- Prototype and deploy novel architectures tailored to biological data, with the freedom to shape strategy and direction.
Requirements:
- First-author publications in top-tier ML/biology journals.
- 6+ years of experience in ML, deep learning, or foundation models (academic or industry).
- Proven expertise with transformers, diffusion, or generative models .
- Strong Python + PyTorch/TensorFlow engineering skills; ability to move from research prototype → production.
- Background in single-cell or omics data is ideal, but ML-first innovators who can quickly learn the biology are very welcome .
- Track record of innovation: new methods, impactful papers, or deployed ML systems.
What We Offer:
- Technical leadership opportunity at a mission-driven company that has recently secured over $50M in funding .
- Work alongside top talent at the cutting edge of AI x biology .
- Chance to impact millions of lives by redefining how cell therapies are developed .
- Competitive compensation and benefits, with an emphasis on urgency, collaboration, and innovation.