Build and own the ML infrastructure that makes our AI systems reliable and improvable, including eval frameworks, prompt management, and model observability
Ship customer-facing AI features on a consistent cadence, balancing new capability delivery with foundational infrastructure work
Define and implement the team's approach to evals, LLM routing, prompt engineering, and model selection
Build pragmatic standards that improve quality without slowing the team down
Contribute to ML technical direction by proactively surfacing trade-offs and architectural options, helping the team make informed decisions on where ML is headed.
Requirements
4+ years of experience in ML or AI engineering, with a track record of shipping production ML systems
Strong hands-on expertise with LLMs, prompt engineering, evals, and model routing
Experience building tooling and systems that have real customer impact
Pragmatic about tradeoffs: knows when good enough is the right call and avoids over-engineering; would rather ship something useful today than design something perfect next quarter
Comfortable working with moderate direction in ambiguous environments, you can take a scoped problem, work through it, and deliver a shipped solution
Builds with the end user in mind; understands how ML decisions impact real customers and prioritizes customer value over technical elegance
Elevates teammates through code review, pairing, and clear communication about technical decisions.
Benefits
Competitive compensation with premium benefits and equity package.