Data Infrastructure Engineer at Pivot Robotics (San Francisco, CA)
Pivot Robotics· San Francisco, CA·
Role details
Work type
Onsite
Employment
Full-Time
Job description
Responsibilities
- Design and own the schemas and data models behind our production systems
- Build and maintain data infrastructure on AWS
- Build the artifact store for scans, meshes, model checkpoints, and calibration files
- Build edge-to-cloud pipelines between robotic cells and our infrastructure
- Build ML infrastructure: training pipelines, dataset versioning, and model deployment
Requirements
- 2+ years building data infrastructure on AWS (application-side, not platform operations)
- Strong schema design and data modeling, including distributed systems tradeoffs
- ML infrastructure experience
- Ability to work across the stack, from analyzing data to designing the systems around it
- Willingness to travel to customer sites
Preferred
- Data infrastructure in a robotics, autonomy, or industrial IoT setting
- Edge computing experience
- Interest in manufacturing
Why work at Pivot Robotics
- Hard problems with real impact: Work on cutting-edge vision-guided robotics in challenging environments (foundries, aerospace). The code you ship gets used daily in production.
- Team: Small, high-caliber team of engineers from Uber ATG, Meta, Google X, Nimble Robotics, and ABB. Founders are former Meta robotics engineers and Carnegie Mellon graduates.
- Culture: Ownership mentality, execution focus, comfort with "real-world messiness." They value first-principles problem solving and deep technical expertise.
- Work environment: Hybrid workspace – employees combine remote and on-site work. Main office in San Francisco, CA, with a robot operator internship site in New Boston, Ohio.
- Perks: Not explicitly detailed, but the culture emphasizes autonomy, cutting-edge robotics, and solving meaningful manufacturing challenges.