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 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 will be a high agency role designed for a builder who wants to operate as a founding member of a new functional group.
Please note: No biology or life sciences background is required for this role.
Position Responsibilities:
You will drive the engineering vision behind our machine learning models, from identifying high-impact research engineering opportunities to delivering production-grade systems. Partnering closely with biology-fluent ML researchers and Data Engineers, your responsibilities will span 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
Position 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)
The estimated base salary range for this role is $220,000 - $290,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.