Senior / Staff Machine Learning Infrastructure Engineer
Calico Life Sciences · South San Francisco, CA
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 / Staff Machine Learning Infrastructure Engineer to productize machine learning algorithms and build a cutting-edge computing and machine learning platform for analyzing biological data sets and modeling macromolecule sequences and structures. You will contribute to a cross-functional effort to create a world-class computing and data analysis platform that supports research initiatives at Calico through the following:
- Develop and optimize: Build software infrastructure and tools that accelerate ML research, manage training and inference workflows, and facilitate efficient data ingestion and curation
- Define engineering best practices: Lead efforts to reorganize and refactor existing research codebases to improve code quality and reproducibility
- Collaborate for impact: Work closely with our ML research scientists to deploy models that address critical questions in aging research and advance Calico's mission
The ideal candidate will possess substantial expertise in designing, developing, and maintaining scalable and reliable ML infrastructure components, encompassing data pipelines, model training and deployment systems, and monitoring tools. Candidates should have a demonstrated track record of optimizing ML workflows for performance and resource utilization. Candidates should remain up to date on best practices for ML model management, versioning, and reproducibility. Candidates must demonstrate a strong ability to communicate ideas and results and collaborate across functions to execute complex projects.
Position Requirements:
- Ph.D. in Computer Science, or related technical field, plus 4+ years of industry experience; or M.S. in Computer Science, or related technical field, plus 7+ years industry experience
- Strong software engineering skills and substantial expertise in Python
- A strong background in designing, developing, and maintaining ML infrastructure components in a production environment
- Experience in productionize ML models developed in Jax, Tensorflow, or Pytorch
- Proficiency in building data pipelines, model training and deployment systems, and monitoring tools
- Excellent problem-solving and analytical skills
- Understanding of distributed systems and parallel computing
- Track record of outstanding communication and collaboration in a cross-functional environment
- A desire to stay current with the latest ML infrastructure technologies and best practices
- Must be willing to work onsite at least four days a week
Nice To Have:
- Domain expertise in computational biology, biochemistry or structural biology
- Prior experience working with biological data
- Experience in working with Google3
The estimated base salary range for this role is $217,000 - $265,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.