Own end-to-end execution of ML programs across data collection, labeling, training, evaluation, and on-device deployment—defining scope, milestones, risks, and success metrics tied to accuracy, latency, and in-store experience.
Build and maintain cross-functional plans with computer vision/ML, Android, hardware, MLOps, data engineering, QA, and field operations; run cadences, surface tradeoffs, and drive on-time, high-quality releases.
Lead data operations at scale, including in-store capture, synthetic generation, and third-party annotation—setting data quality bars, SLAs, and privacy standards in partnership with Legal and Security.
Establish rigorous evaluation frameworks that connect offline metrics and on-device performance to business outcomes (e.g., recognition accuracy, shrink reduction, throughput), including pilots and A/B tests in stores.
Drive deployment readiness and reliability: model packaging for edge devices, rollout plans, monitoring and alerting, incident response, and postmortems with clear, actionable follow-ups.
Communicate program status and insights to stakeholders and executives; proactively manage dependencies and risks across a ~25-person cross-functional org and external vendors.

Requirements

6+ years of technical program management experience, ideally leading end-to-end ML/AI programs from data to production.
3+ years working on computer vision or edge/on-device ML for embedded, mobile, or hardware-integrated products.
Proven track record delivering 3+ production ML model releases or ML-powered features with measurable impact on product metrics.
Bachelor’s degree in Computer Science, Electrical/Computer Engineering, or a related technical field; or equivalent practical experience.
Hands-on familiarity with the ML lifecycle, including data pipelines, labeling/annotation workflows, model training/evaluation, and MLOps/CI-CD for ML.
Ability to query and analyze data using SQL and basic Python to validate assumptions and interpret model and product performance.
Experience coordinating cross-functional teams of 10+ stakeholders, including external vendors, with strong risk, dependency, and change management.
Excellent written and verbal communication skills, including executive-level reporting and decision facilitation.
Willingness to travel to stores, labs, and partner sites as needed (up to 15%).

Benefits

Highly market-competitive compensation and benefits
Remote work options
Flex First remote work policy

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningcomputer visiondata pipelinesmodel trainingmodel evaluationMLOpsCI-CDSQLPythondata labeling

Soft Skills

program managementcross-functional collaborationrisk managementdependency managementchange managementcommunicationstakeholder managementdecision facilitationanalytical thinkingproblem solving