Data Operations Lead
HappyRobot - San Francisco, California, United States
Posted May 4, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Data Operations Lead San Francisco, California, United States About HappyRobot HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide. Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto. Role Overview: Working hand-in-hand with Engineering, Data Ops tackles two critical challenges: identifying the exact data required to build industry-leading AI audio models, and figuring out how to acquire and scale that data efficiently. As a key member of this team, you will drive the complete lifecycle of our data collection and annotation efforts. You will act as the vital link between research objectives and daily operations, coordinating both internal teams and external vendors to ensure top-tier datasets are delivered on schedule. Furthermore, you will help expand our operational capacity by upgrading our tools, streamlining workflows, and nurturing a high-performing team of data labelers. Key Responsibilities: - Translate Research Needs: Convert complex research requirements into clear, actionable data specifications and labeling workflows. - Manage End-to-End Operations: Oversee the full
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