Senior Machine Learning Research Engineer (ML Platform)

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico's highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico seeks a Senior Machine Learning Research Engineer to join the team building the computational engine that closes the design-test-learn cycle in molecular design and scales the ML infrastructure across the company.

Working closely with a biology-fluent group of researchers and engineers, you will build ML platforms to accelerate their research, translate advanced ML methods into scalable code, and iteratively refine these tools as they apply them to real-world drug discovery problems.

If you are passionate about building high-impact ML systems, thrive in ambiguity, and are excited to move fluidly between optimizing data pipelines and deploying generative models, this is the role for you.

Please note: No biology or life sciences background is required for this role.

Key Responsibilities:

You will own the end-to-end flow from data ingestion to model deployment. Because of the flexible nature of this role, your responsibilities will adapt to the team's most pressing needs, shifting between two core areas:

ML Platform

• Build and scale core components of our ML Data, Eval, and Serving platforms, including APIs, libraries, and datastores
• Optimize the training and serving stack to maximize accelerator utilization at scale
• Automate end-to-end ML workflows between computational models and the wet lab, ensuring full reproducibility and lineage tracking

Generative Modeling & Search

• Optimize and scale our molecular search methods
• Identify opportunities to accelerate model research workflows and ship tools quickly
• Prototype new modeling ideas with researchers and deploy them into the drug discovery pipeline

Position Requirements:

• A strong intellectual curiosity for life sciences
• 5+ years of relevant ML software engineering experience in industry or academia
• Strong software engineering skills, particularly building model training, serving, or evaluation platforms
• Deep expertise in Python and JAX or PyTorch
• Must be willing to work onsite at least four days a week

Nice to Have:

• Large-scale data processing experience (e.g., Ray, Spark, BigQuery) and high-throughput data loading
• Familiarity with common biological datasets and formats (e.g., BAM, TIFF, Zarr, AnnData)
• Hands-on experience with advanced ML architectures (e.g., transformers, diffusion networks), search and optimization methods (e.g., active learning, Bayesian optimization, RL), or large-scale biomolecular models (e.g., AlphaFold)
• Advanced degree in computer science or a relevant field
• Contributions to open-source ML projects or relevant academic publications

The estimated base salary range for this role is $209,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.