Autonomy AI Data Operations Lead

Rivian Automotive; Palo Alto (CA); On-site; USD 213,000 - 266,000; Full time

Job summary

Rivian Autonomy is seeking an AI Data Operation Lead to head the teams turning vehicle data into reliable training and evaluation datasets. You will lead labeling delivery, data quality, curation, and human review to support our autonomous driving models.

You will supervise internal teams and external partners, ensure data is usable and labels meet model requirements, and turn difficult driving events into actionable feedback for engineering.

Qualifications

• 10+ years leading operations, incl. 5+ years in AV/robotics/ML with budgets or P&L.
• Experience managing annotation partners across domestic and international locations.
• Depth in AI development to discuss data requirements with engineers.
• Record of developing managers and specialists and adapting teams.
• Strong analytical judgment to separate quality vs capacity or tooling problems.
• Clear communication across engineering, product, finance and operations.

Responsibilities

• Lead the organization: set operating plan, build capacity across teams and vendors.
• Deliver data that model teams can use: translate needs into labeling specs and milestones.
• Improve data quality and yield: ensure readiness and resolve data-quality issues.
• Own vendor performance and spend: set SLAs, manage budgets and invoices.
• Develop human evaluation and triage operations: build review workflows and feedback.
• Run the operation with metrics: track volume, quality, turnaround, backlog, cost.
• Improve tools and automation: collaborate on labeling tools and quality checks.

Skills

Data ops leadership

Budget management

Vendor management

Cross-functional

AI data quality

Job description

Rivian Autonomy is seeking an AI Data Operation Lead to head the teams turning vehicle data into reliable training and evaluation datasets. You will lead labeling delivery, data quality, curation, and human review to support our autonomous driving models.

You will supervise internal teams and external partners, ensure data is usable and labels meet model requirements, and turn difficult driving events into actionable feedback for engineering.