Senior/Principal Machine Learning Engineer

Responsibilities

• Interpret qualitative challenges in building AI agents for science as well-formulated optimizable problems
• Build appropriate environments in which to train and deploy AI agents that solve scientific tasks
• Work with scientists to formulate training data pipelines, and scale them, ensuring observability and reproducibility
• Lead training of large-scale LLM-based systems, including building internal infrastructure to improve the efficiency of experimentation and production training runs
• Develop and extend our experimentation platform for internal tools and projects
• Collaborate closely with a multidisciplinary team of AI researchers, chemists, biologists, fostering an environment of innovation and discovery

Qualifications

• 5-10+ years of strong track record of work in applied ML research and application of ML methods to solving real-world problems
• Experience working across the ML lifecycle: data pipelines and provenance, model training, model deployment, and validation in production systems
• Fluency in PyTorch, Jax or equivalent framework
• Demonstrated experience with experimentation in academic or industry settings
• Strong programming expertise with the capability to adapt to various technical challenges in the data, ML, and LLM software stack
• Bonus points for PhD in Machine Learning, Computer Science, or other quantitative field
• Familiarity with leveraging and managing distributed computing resources
• Background architecting complex distributed systems

Pay

$240,000 - $350,000 Offers equity

Schedule

On-site at our San Francisco office in the Dogpatch neighborhood