Technical Product Manager, Data Infrastructure
Lightwheel
- Location
- Mountain View
- Employment
- Full Time
- Work model
- Remote
- Level
- Mid
- Posted
- 1h ago
Skills
About this role
About the Role
We are looking for a Technical Product Manager, Data Infrastructure to own strategic customer data deliveries and help build Lightwheel’s Data Delivery Platform into scalable, reusable infrastructure.
Responsibilities
Own Data Platform — Define and evolve data schemas, validation, adapters, conversion, cloud transfer, APIs/SDKs, observability, and cost optimization. Drive Customer Delivery — Translate customer requirements into technical specifications, acceptance criteria, and delivery plans; own programs end-to-end through customer acceptance. Scale Data Operations — Build systems and processes capable of supporting 100K–1M+ data-hour programs with predictable throughput, reliability, and cost. Solve Complex Technical Problems — Identify and resolve bottlenecks across compute, storage, networking, data pipelines, APIs, and customer ingestion. Build Scalable Processes — Standardize delivery workflows, quality gates, versioning, and change management to make customer onboarding repeatable and scalable. Lead Cross-Functional Execution — Work closely with Engineering, Data Operations, Infrastructure, and customers to drive technical delivery and continuously improve the platform.
Qualifications
3+ years of experience in software engineering, data infrastructure, distributed systems, ML/robotics infrastructure, or customer engineering. Strong hands-on engineering background with Python, APIs/SDKs, AWS/GCP, Kubernetes, and data pipelines . Experience building or operating production data platforms or large-scale data pipelines . Strong problem-solving skills with the ability to diagnose bottlenecks across compute, storage, network, and APIs . Experience working directly with technical customers and leading cross-functional projects. Fluent in English and Mandarin.
Preferred Qualifications
Experience in robotics, autonomous driving, embodied AI, or Physical AI . Experience with large-scale video, sensor, multimodal, or ML training datasets . Familiarity with LeRobot, MCAP, ROS bags, TB/PB-scale data, or cloud data transfer . Experience in forward-deployed engineering, enterprise data integration, or building infrastructure functions from the ground up .