5+ years of experience in quality control, preferably in AI or data-driven environments
Strong technical background with hands-on experience in auditing datasets
Familiarity with reinforcement learning (RL) trajectories, code, and reasoning data
Proven ability to work independently and make critical decisions
Experience in building quality processes and metrics from the ground up
Responsibilities
Own the final quality checkpoint before delivery by auditing datasets for correctness and adherence to specifications
Build the QC function from scratch, defining review processes and grading criteria
Partner with Pod Leads to identify systemic quality issues and improve contributor training
Collaborate with infrastructure engineers to automate QC workflows
Manage quality metrics and KPIs, reporting trends and root causes to leadership
Benefits
Open to visa transfers (e.g., OPT, H1B transfers)
On-site work policy of 5 days in-office in San Francisco
Opportunity to shape the quality control function from the ground up
Direct reporting to the Head of Operations, influencing company-wide quality standards
Work in a high-growth startup environment with potential for significant impact
Full Job Description
Salary range: $150K - $275K
Location: San Francisco, CA
Visa Sponsorship Details: Open to visa transfers (e.g. OPT, H1B transfers)
On-site work policy: 5 days in-office in SF
About this role
We are looking for a Quality Control Lead with experience doing hands-on QC of technical or human data, ideally at an AI lab, data company, or high-growth startup, to become our first dedicated quality hire. Today our Pod Leads handle quality review on top of their other work. You'll build a separate internal audit layer that checks every dataset before it reaches the frontier AI labs we serve. We want someone sharp and technical who knows what high-quality data looks like, whether that's RL trajectories, code, or reasoning data, and who can work independently from day one. You'll report directly to our Head of Operations and decide what's good enough to ship.
What you will be doing
Owning the final quality checkpoint before delivery - auditing code, reasoning, and RL trajectory datasets for correctness, structure, and adherence to spec
Building the QC function from scratch - defining review processes, rubrics, and grading criteria as the company's first dedicated quality hire
Partnering with Pod Leads and data delivery teams to find systemic quality issues and feed corrections back into contributor training
Working with infrastructure engineers to automate QC workflows and tooling so the same errors don't happen twice
Owning quality metrics and KPIs - reporting error rates, root causes, and improvement trends to the Head of Operations and leadership
