Member of Technical Staff, Machine Learning Engineer
Edison Scientific2 days ago
Base Salary
$240k - $350k/yr
Responsibilities
- Formulate scientific AI-agent challenges as optimizable problems and build environments for training and deployment.
- Develop scalable training-data pipelines with observability and reproducibility.
- Lead training of large-scale LLM-based systems and build infrastructure for experimentation and production training runs.
- Build flexible inference infrastructure supporting complex sampling algorithms and custom architectures.
- Extend internal experimentation platforms and collaborate with AI researchers, chemists, and biologists.
Requirements
- 5-10+ years of applied ML research and experience applying ML methods to real-world problems.
- Experience across the ML lifecycle, including data pipelines and provenance, model training, deployment, and production validation.
- Fluency in PyTorch, Jax, or an equivalent framework.
- Demonstrated academic or industry experimentation experience.
- Strong programming expertise across data, ML, and LLM software systems.
- Preferred: PhD in Machine Learning, Computer Science, or another quantitative field.
- Preferred: experience managing distributed computing resources and architecting complex distributed systems.
Benefits
- $240,000-$350,000 salary plus equity.
- Full healthcare coverage with 100% of premiums paid for employees and dependents.
- New parent stipend, fertility coverage through Carrot, mental health support through Rula, and 12 weeks of paid parental leave.
- Employer-funded pet care stipend, commuter benefits, and 401(k) company matching.
- $300 quarterly health and wellness benefit.
- Free lunch while in the office and dinner when working late.
- Regular team off-sites and company events.
Tech Stack
Categories
About Edison Scientific
Edison Scientific builds AI scientist agents and an R&D platform (Kosmos) for pharma, biotech, and materials teams, integrating with organizations’ proprietary data to guide experiments and analysis from discovery through development. Headquartered in San Francisco and privately held, it was spun out of the nonprofit research lab FutureHouse in 2025, and offers enterprise deployments—including bring-your-own-cloud installations—to meet compliance requirements at large research organizations.