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Uber

Staff Software Engineer - ML Infra

Posted 4 Days Ago
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In-Office
Sunnyvale, CA
232K-258K Annually
Senior level
In-Office
Sunnyvale, CA
232K-258K Annually
Senior level
Develop scalable ML infrastructure for autonomous vehicle use cases within Uber AV Labs. Responsibilities include designing multi-region, multi-cloud platforms; customizing Uber’s ML platform; aligning infrastructure and AV teams; executing technical projects from conception through production; and optimizing GPU efficiency. The role requires expertise in CUDA, TensorRT, Kubernetes, Flyte or Airflow, and Ray, along with at least six years of experience and a computer science degree.
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About the Role

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We’re building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team will be focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race–and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match (millions of Uber trips every hour across cities, conditions, and edge cases create the data autonomy has been missing).

 

We will build platforms that harness scale and real-world complexity to reimagine how the world moves.

You will be a software engineer in AV Labs and involved in the development and implementation of the latest technology for self-driving stacks. The ideal candidate will be able to identify issues, provide solutions, and implement the fixes, as well as set a high technical excellence bar in all things we do.

What the Candidate Will Do:
  • Work with Uber’s ML platform and design customized solutions for AV use cases.
  • Design and implement scalable infrastructure on multiple regions and multiple cloud providers.
  • Lead stakeholder alignment with Uber infrastructure teams and AV Labs teams.
  • Drive efficiency efforts on GPUs.
Basic Qualifications:
  • Minimum 6 years of working experience.
  • Proven experience for executing technical projects from conception to production.
  • Bachelor’s degree in Computer Science or related fields.
  • Familiar with GPU technologies: CUDA, TensorRT, GPU optimizations
  • Familiar with compute cluster management: Kubernetes
  • Familiar with batch orchestration: Flyte or Airflow
  • Familiar with distributed batch processing: Ray
Preferred Qualifications
  • Master or PhD degree in Computer Science or related fields.
  • Background in ML Platform teams from large companies.
Responsibilities

For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

About Us

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

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