Data Quality & Annotation Lead — Equity

Nimble; San Francisco (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Unlimited Flexible Time Off

Health Insurance

Referral Bonus

401k

Equity

Job summary

Nimble is seeking a Manager, Data Quality & Annotation to establish and scale the quality bar for real-world operational data used to train our autonomous robots. The role combines defining acceptance criteria, building audit workflows, and standing up a remote annotation team to ensure labeled data flows to research on schedule.

You will own rubrics, audits, dashboards, and a standing weekly loop with research and engineering to address failure modes and drift.

Qualifications

• 3+ years in data ops, annotation, or data collection QA for ML systems — robotics, autonomy, or teleoperation data preferred.
• Track record building quality standards from scratch — rubrics, SOPs, QC workflows.
• Experience managing annotation or review teams, including remote/offshore or vendor/BPO, and meeting SLAs.
• Experience delivering direct, frequent quality feedback to operators/annotators, including tough conversations.

Responsibilities

• Own episode acceptance criteria for every task family — translate research/engineering needs into auditable standards and version them.
• Take over the annotation and episode-review queue early on, then scale the team and workflows beyond a single contributor.
• Stand up and manage a remote annotation team with an overnight turnaround SLA.
• Design and run a sampling-based QA audit program with coverage targets and inter-rater reliability checks.
• Run the operator quality feedback loop: 24-hour delivery of quality scorecards to site supervisors.
• Define quality metrics and build the dashboards the team relies on with the analytics function.
• Own the certification bar for new operator onboarding and ensure production data collection meets it.
• Drive a weekly loop with research/engineering on failure modes and task drift.

Skills

Data ops

Annotation

QA workflows

Remote management

SQL

BI tools

Offshore teams

Reporting

Tools

Annotation software

QA tooling

Job description

Nimble is seeking a Manager, Data Quality & Annotation to establish and scale the quality bar for real-world operational data used to train our autonomous robots. The role combines defining acceptance criteria, building audit workflows, and standing up a remote annotation team to ensure labeled data flows to research on schedule.

You will own rubrics, audits, dashboards, and a standing weekly loop with research and engineering to address failure modes and drift.