ML Data Operations Engineer

What you'll do

• Plan, execute, and track internal machine learning data collection studies with researchers and engineers.
• Develop a technical understanding of ML experiments, including model objectives, labeling requirements, and evaluation criteria.
• Bring up and maintain pre-release hardware and software platforms while performing hands-on troubleshooting to minimize disruptions.
• Create and maintain technical documentation for platform setups, study protocols, and data handling procedures.
• Manage daily logistics for internal study sessions, including participant scheduling and hardware configuration.
• Validate data collection requirements with algorithm, infrastructure, and hardware teams before and during execution.
• Track and communicate study progress, blockers, and dataset status to cross-functional partners and stakeholders.
• Identify gaps in existing workflows and develop documented process improvements.

What we're looking for

• Bachelor's degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent experience.
• Experience supporting or executing human user studies, behavioral research, or data collection operations.
• Track record of partnering with ML engineers or researchers to define data requirements and quality standards.
• 10 years of experience in user research operations, data collection coordination, or a related technical operations role.
• Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices.
• Experience working with engineering and science teams while reading technical documentation and data schemas.
• Familiarity with handling sensitive human data and adhering to strict privacy and consent protocols.
• Strong interpersonal and written communication skills for collaborating across technical and non-technical stakeholders.