ML & Cloud Infrastructure Engineer Intern

Role: ML & Cloud Infrastructure Engineer Intern

Location: SF Bay Area (in-person)

Our internships are scoped projects: you own a defined deliverable end‑to‑end, work with a dedicated mentor, and demo your work to the whole team. Many interns receive return or full‑time offers. This internship will last either 3 months or 6 months. We offer competitive salaries and the opportunity to work on a mission with tremendous climate impact.

• Build and operate training, data, or evaluation infrastructure used daily by the wider SW team.
• Work with GPU clusters, orchestration, and data pipelines at scale.
• Instrument, monitor, and harden the pipeline you ship.
• Test your work on real robots at the office.
• Opportunity to publish (for PhD interns).
• Attend Tier‑1 industry conferences.

An example project could be anything from an auto‑curation pipeline that mines fleet logs for rare events (gusts, occlusions, near‑misses) to feed training, to a regression harness that replays field scenarios against each new model release.

• Pursuing BS/MS/PhD in CS or related field.
• Strong Python; familiarity with cloud services (AWS/GCP), containers, and CI/CD.
• Evidence of building infrastructure or data systems.
• Comfortable taking ownership of tasks with light supervision.
• Excellent problem‑solving skills.
• Legally authorized to do an internship in the United States for either 3 months or 6 months.

• Kubernetes, Ray, Spark, Terraform, observability stacks, or ML experiment tooling.