Builds scalable data collection pipelines and interfaces for AI model improvement, collaborating with researchers and data operations. Requires strong full-stack engineering, internal tooling expertise, and adaptability in fast-paced research environment.
320k – 405k/yr
HybridFullstack Engineering
About the role
Responsibilities:
Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability
Think deeply about the experience of crowdworkers and vendors, building clear, efficient interfaces for high-quality data
Collaborate with research teams to understand evolving data needs and iterate quickly
Partner with Human Data Operations to design interfaces that streamline end-to-end workflows
Prioritize and juggle multiple workstreams in a fast-moving environment
You May Be a Good Fit If You:
Are a strong full-stack engineer with broad experience
Excel at building internal tools and understanding user needs
Thrive in fast-moving environments balancing speed and system health
Are a quick study across complex technical systems
Strong Candidates May Also Have:
Experience with human data labelling interfaces, human-in-the-loop systems, or data collection pipelines
Familiarity with preference data and reward models in AI training
Experience working with researchers as internal users
Background in user-facing applications with complex UI or annotation workflows
Strong system design instincts for evolving requirements
Experience influencing technical and product direction
Logistics
Education requirements: At least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Expect to be in office at least 25% of the time.
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