Salary
$150k – $240k per year
Location
In office (San Francisco)
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 5, 2026.
Overview
Company
Impact
Profile match
Success Matcher is a global recruitment and talent advisory firm registered in Helena, Montana, that sources candidates for client companies, many of them venture-backed technology start-ups, across North America, Europe and Asia. It recruits for clients on permanent and on-demand terms, with most current searches in San Francisco and New York and others in London, Washington, Houston, Atlanta and Manila. Its vacancies, filled on behalf of clients, include account executives, sales engineers and business development representatives, AI, robotics and electrical engineers, data scientists, implementation managers and procurement managers, as well as internal recruiters.
About the Role
Our client is a Y Combinator-backed, seed-stage AI data research lab building the data layer for reinforcement learning. They build synthetic data pipelines and simulation environments that enable frontier AI models to learn and reason. Instead of writing traditional application PRDs or managing feature backlogs, you will act as the PM of the model itself-co-designing capabilities alongside elite AI researchers.
Key Responsibilities
- Co-design model capabilities alongside researchers and diagnose performance gaps in long-horizon coding, cybersecurity, and ML chip design.
- Architect synthetic data pipelines and simulation environments using our client's proprietary engine to address model weaknesses.
- Execute experiments and benchmarks using internal simulation stacks and open-source tooling.
- Engage directly with researchers at top AI labs and Fortune 500 enterprises to identify where state-of-the-art models fail in real-world scenarios.
- Influence the product roadmap, go-to-market strategy, and overall research direction based on evaluation metrics.
Requirements
- Hands-on project experience with RL training data, synthetic data generation, or simulation environments.
- Proven ability to diagnose model failure modes and build targeted training data solutions.
- Strong technical fundamentals (CS degree, ML background, or equivalent) with the ability to read code and understand model architecture.
- Direct experience running ML experiments and interpreting benchmarking data.
- High drive and adaptability suited for an early-stage, fast-moving meritocracy.
Compensation & Benefits
- $150,000 - $240,000 base salary + performance bonus + meaningful early-stage equity.
- Full health, dental, and vision coverage.
- Flexible PTO.
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