3 months ago
Responsibilities
- Turn interpretability research into production-ready product features in partnership with researchers and machine learning engineers.
- Build and own full-stack features, APIs, workflows, and interfaces from ambiguous ideas through product delivery.
- Create performant, reproducible, observable, reliable, and stable product systems for real customer use.
- Shape product direction by identifying improvements, proposing better workflows, and helping determine what to build next.
- Integrate product features with infrastructure for model analysis, training, inference, and experimentation.
Requirements
- At least 2 years of experience building production software, particularly user-facing products, data-intensive systems, or AI/ML products.
- Strong engineering fundamentals with depth in at least one of frontend, backend, systems, or product infrastructure.
- Strong product judgment and an ability to make complex technical systems clear, reliable, and easy to use.
- Ability to collaborate across research, engineering, design, and customer-facing teams.
- Interest in understanding model internals and applying that understanding to make AI systems more reliable and useful.
- Preferred: experience building products for technical users such as developers, researchers, machine learning engineers, or infrastructure teams.
- Preferred: startup or frontier-lab experience in fast-moving teams.
Benefits
- In-person work at the San Francisco headquarters five days per week, with one company-wide remote week per month.
- Market-competitive salary, equity, and competitive benefits.