Machine Learning Engineer – Biological Foundation Models

Machine Learning Engineer – Biological Foundation ModelsMetric 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.Check below to see if you have what is needed for this opportunity, and if so, make an application asap.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. xmcpwfuCompetitive compensation and benefits, with an emphasis on urgency, collaboration, and innovation.