Senior Product Manager, Labeling

Role Overview

• Own the long‑term product vision and roadmap for GM’s data labeling ecosystem, covering human‑in‑the‑loop labeling tools, workflow orchestration, and automatic labeling technologies.
• Define UI and workflow requirements for labeling tools that maximize annotator efficiency, reduce errors, and ensure consistent quality across large‑scale labeling operations.
• Develop a strategy and roadmap for automatic and semi‑automatic labeling, including model‑assisted tools, heuristics, and quality‑gating mechanisms.
• Partner with AV and ADAS ML teams to deeply understand their data modalities, annotation requirements, and pain points—translating these into clear product requirements and prioritization frameworks.
• Drive efficiency investments for human labelers, including process optimization, intelligent task routing, active‑learning loops, and targeted improvements based on productivity metrics.
• Balance cost, throughput, and quality when choosing between human, hybrid, and automated labeling solutions.
• Lead cross‑functional efforts across Engineering, Operations, ML Research, Design and Program teams to deliver scalable, reliable, and secure labeling infrastructure.
• Establish KPIs that measure labeling quality, annotation velocity, end‑to‑end cycle time, ML impact, and cost efficiency—and use them to inform product decisions.
• Act as the voice of labeling customers (ML engineers, data scientists, and safety evaluators), ensuring labeling solutions support their development cycles, evaluation workflows, and model iteration velocity.

Requirements

• 5+ years of product management experience, ideally in data labeling, ML tooling, annotation platforms, or related areas.
• Demonstrated ability to translate the needs of ML customers into actionable product requirements and technical tradeoff frameworks.
• Strong product judgment with experience solving complex, constrained problems using structured reasoning and data‑informed decisions.
• Experience defining workflow and UI requirements for technical or operations‑heavy tools, with a focus on efficiency, usability, and quality outcomes.
• Ability to balance competing factors across annotation quality, throughput, cost efficiency, and ML impact.
• Strong written communication skills, with the ability to integrate engineering, safety, privacy, and operational perspectives into clear narrative requirements.
• Experience identifying and instrumenting key metrics for labeling efficiency, model‑assisted workflows, and ML training effectiveness.
• Ability to work across engineering, operations, and research teams to build alignment on roadmap priorities and deliver cross‑functional outcomes.

Benefits

• GM offers a variety of health and wellbeing benefit programs.
• Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.