Senior / Staff Machine Learning Research Engineer

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 its vibrant drug-development pipeline with academic and industry partners create an inspiring and exciting place to catalyze and enable medical breakthroughs.

About the role

Calico seeks Machine Learning Research Engineers to join our rapidly growing ML team. You will play a critical role establishing the engineering culture for frontier ML research in drug discovery. You will bring a high level of engineering rigor to our machine learning efforts and accelerate our research maturing into tangible clinical and product impact. This is a high-agency role designed for a builder who wants to operate as a founding member of a new functional group. No biology or life sciences background is required.

Responsibilities

• Drive the engineering vision behind our machine learning models, from identifying high-impact research engineering opportunities to delivering production-grade systems.
• Partner closely with biology-fluent ML researchers and Data Engineers across the following areas:
  • Research Engineering: Proactively identify emerging engineering gaps required for expanding our research capabilities. Architect solutions for complex systems challenges, such as asynchronous execution, hardware orchestration, and high-throughput data pipelines. Build foundational libraries that enforce software engineering rigor.
  • Model Implementation and Optimization: Translate prototype models (e.g., diffusion networks, vision transformers, and DNA sequence models) into highly-optimized JAX or PyTorch code on accelerators. Dive deep into model architectures to optimize training and inference performance, implementing advanced strategies such as model parallelism.
  • Force Multiplier: Design and implement evaluation frameworks, benchmarks, and scientific workflow tools that accelerate the research lifecycle and allow the team to rapidly test promising ideas.

Requirements

• A strong intellectual curiosity for life sciences.
• BS/MS with 7+ years or PhD with 4+ years of relevant ML software engineering experience in industry or academia.
• Expertise in Python and JAX or PyTorch.
• Hands-on experience building, training, or optimizing advanced ML architectures (e.g., transformers, diffusion networks, GNNs).
• Experience driving complex machine learning engineering projects from concept to production.
• Must be willing to work onsite at least four days a week.

Nice to Have

• Advanced degree in computer science or a relevant field.
• Experience working with biological, medical, or chemistry datasets.
• Contributions to open-source ML projects or relevant academic publications.
• Experience training models across distributed systems and optimizing performance.
• Experience with cloud infrastructure (e.g., GCP, Kubernetes, Docker).

Pay

The estimated base salary range for this role is $220,000 - $290,000. Actual pay will be based on experience and qualifications. This position is also eligible for two annual cash bonuses.