ML Data Operations Engineer

What you'll do

• Plan, execute, and track internal machine learning data collection studies in collaboration with researchers and engineers.
• Develop a technical understanding of ML experiments, including model objectives, data requirements, and evaluation criteria.
• Bring up and maintain pre-release hardware and software platforms used for data collection.
• Perform hands-on troubleshooting and triage to minimize disruptions during study execution.
• Create and maintain technical documentation for platform setup, study protocols, and data handling procedures.
• Manage daily logistics of internal study sessions, including participant scheduling and hardware configuration.
• Communicate study progress, blockers, and dataset status to cross-functional partners and senior stakeholders.
• Identify gaps in existing workflows and implement process improvements for data collection operations.

What we're looking for

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