Robotics & AI Data Platform PM

Success Matcher Recruitment; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Success Matcher Recruitment is seeking a Data Technical Product Manager to own the end-to-end data platform that powers next-gen ML systems. You will drive the data lifecycle from capture to training, partnering with ML teams and engineers to scale infrastructure for large datasets.

The role requires translating ambiguous technical needs into concrete plans, establishing data quality standards, and coordinating across vendors and researchers to deliver high-quality training data.

Qualifications

• 4+ years of Technical Product Management experience.
• Experience with large-scale data operations and data pipelines.
• Experience supporting applied machine learning or AI systems.
• Strong understanding of data quality, governance, and labeling processes.
• Ability to translate ambiguous requirements into actionable plans.
• Proven track record coordinating across engineering, research, operations, and vendors.

Responsibilities

• Own the end-to-end data platform roadmap and lifecycle from capture to delivery into ML training pipelines.
• Partner with ML teams to translate research requirements into data collection and annotation specs.
• Define dataset requirements and collection strategies to support model development.
• Establish data quality standards, QA frameworks, and validation workflows.
• Manage data annotation operations including third-party vendors and quality metrics.
• Develop data discovery and infrastructure capabilities for cataloging, search, and dataset management.
• Design feedback loops that surface edge cases and improve data collection efficiency.

Skills

Technical Product Management

Large-Scale Data Operations

End-to-end Data Pipelines

ML/AI Systems Experience

Data Quality & Governance

Ambiguity Management

Cross-functional Leadership

Job description

Success Matcher Recruitment is seeking a Data Technical Product Manager to own the end-to-end data platform that powers next-gen ML systems. You will drive the data lifecycle from capture to training, partnering with ML teams and engineers to scale infrastructure for large datasets.

The role requires translating ambiguous technical needs into concrete plans, establishing data quality standards, and coordinating across vendors and researchers to deliver high-quality training data.