Edison Scientific

Principal Machine Learning Engineer

San Francisco, CA · Principal

Sponsorship not specified$275k-$350kDetected 135 days ago

Distributed SystemsAlgorithmsMachine LearningPyTorchData EngineeringLLMsAgentic AIA/B TestingResearch

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.

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.

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

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.