Staff Software Engineer - ML Infra

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.