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Salary: USD 150,000 - 300,000 / annual
Roboflow is building the visual cortex for physical AI—tools and platforms that make computer vision accessible to developers worldwide. Over 1M+ developers, including those from Fortune 100 companies, use Roboflow to build and deploy computer vision models for applications ranging from cancer research to construction safety to drone guidance.
As a Member of Operational Staff on the Frontier Data team, you will own the complete delivery pipeline for datasets and environments shipped to leading AI labs and frontier model researchers. This is an end-to-end operational role where you manage the full lifecycle: intake, scoping, process setup, execution, quality review, and final shipment.
Key responsibilities include:
- Own delivery from initial intake through execution, review, and shipment to partners
- Build and enforce processes that make quality visible, measurable, and consistently maintained
- Interface directly with researchers and engineers at leading AI labs to translate requirements into concrete specifications
- Plan and manage capacity across contributor and reviewer networks
- Work with Roboflow engineers to identify automation opportunities and eliminate repetitive work
You are a highly organized operator with strong ownership mentality and bias toward action. You thrive in ambiguity, can translate fuzzy requirements into clear specs, and excel at building scalable processes. Practical experience with agents, evaluations, RL workflows, data labeling, annotation operations, or ML training pipelines is valuable. You bring exceptional organizational skills, sound judgment, and outstanding communication abilities.
Roboflow is a fully distributed company with the Frontier Data team headquartered in San Francisco. The company maintains hubs in NYC, SF, Singapore, and Brazil, with plans to expand. You can work from a hub (relocation bonus available), from home, or from co-working spaces. The company provides a $4,000/year travel stipend and resources to facilitate in-person collaboration across the distributed team.
