ML & Cloud Infra Intern: Build GPU Pipelines for Robotics

Gritt; South San Francisco (CA); Hybrid; USD 33,000 - 47,000; Full time

Job summary

Gritt seeks an ML & Cloud Infrastructure Engineer Intern to help build training and evaluation infrastructure for robotics systems. You will work with GPU clusters, data pipelines, and deployment tooling while shipping measurable improvements to ML workloads.

This internship offers end-to-end ownership with a dedicated mentor and a chance to demo progress to the team. You will gain experience operating in cloud environments (AWS/GCP), developing containerized pipelines, and contributing to

Qualifications

• 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.
• Should be comfortable taking ownership of tasks with light supervision.
• Must have excellent problem-solving skills.
• Legally authorized to do an internship in the United States for either 3 months or 6 months.

Responsibilities

• 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.

Skills

Python

Cloud services (AWS/GCP)

Containers

CI/CD

Infrastructure/data systems

Problem-solving

Ownership

Education

Pursuing BS/MS/PhD in CS or related field

Tools

Kubernetes

Terraform

Spark

Ray

Observability stacks

ML experiment tooling

Job description

Gritt seeks an ML & Cloud Infrastructure Engineer Intern to help build training and evaluation infrastructure for robotics systems. You will work with GPU clusters, data pipelines, and deployment tooling while shipping measurable improvements to ML workloads.

This internship offers end-to-end ownership with a dedicated mentor and a chance to demo progress to the team. You will gain experience operating in cloud environments (AWS/GCP), developing containerized pipelines, and contributing to