Edison Scientific
Principal Machine Learning Engineer
San Francisco, CA · Principal
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DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that.
- You will work on both cutting edge research and practical engineering, bridging advanced machine learning concepts with robust, reliable software that real scientists depend on.
- This role is on-site at our San Francisco office in the Dogpatch neighborhood.
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
- 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.
- Edison Scientific builds and commercializes AI agents for science.
- We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.
- Our office is a converted warehouse with high ceilings, open space, and a team excited about what we're building.
Requirements
- 8-10+ 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.
- 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.
- Familiarity with leveraging and managing distributed computing resources
- Fluency in PyTorch, Jax or equivalent framework.
- Bonus points for
- PhD in Machine Learning, Computer Science, or other quantitative field
- Background architecting complex distributed systems
- $275,000 - $350,000
- Offers equity
- Why join us?
- Competitive salary and equity
- Full healthcare coverage - we pay 100% of premiums for you and your dependents
Compensation
- $275,000 - $350,000 • Offers equity
- Competitive salary and equity
- Full healthcare coverage - we pay 100% of premiums for you and your dependents
Benefits
- Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
- $300 health and wellness benefit
This listing is sourced directly from Edison Scientific's careers page and normalized into a canonical job model.