Drimva

General Motors

Senior Software Engineer, Data Platform (Autonomous Vehicles)

$153K–$269K

Austin, Texas, United States of America +1 · Remote/Hybrid · Senior · Full-time · Posted Oct 15, 2026

Location
Austin, Texas, United States of America
Mountain View, California, United States of America
Experience
5+ years in building and supporting large-scale data platforms.
Education
BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field.
Visa sponsorship
GM does not provide immigration-related sponsorship for this role, now or in the future.

About the job

Build and operate large-scale data platform services that support autonomous-vehicle model training, data mining, labeling, and replay.

What you'll do

  • Own and improve deployment of autonomy data platform services, and lead operational excellence through SLO/SLI measurement and incident response.
  • Translate stakeholder needs into platform requirements, build self-service capabilities, and deliver end-to-end technical projects.
  • Contribute to planning, code reviews, design discussions, interviews, onboarding, and mentoring.

What they ask for

  • BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field.
  • 5+ years building and supporting large-scale data platforms, including high-performance services serving petabytes of weekly data.
  • Expert-level proficiency in Java, C++, Go, or Python, with experience designing and implementing distributed systems.
  • Experience managing services on at least one major public cloud provider (Azure, GCP, or AWS), and optimizing service cost, performance, and reliability.

Nice to have

  • Experience implementing Beam or Spark data processing frameworks and high-throughput, low-latency serving layers.
  • Experience with 100+ petabyte-scale architectures or SQL engines/queries; interest in self-driving technology.

Pay

$153,200 - $269,200 USD base salary

Tools

Java, C++, Go, Python, Azure, GCP, AWS, Beam

AI focus

Supports autonomous-vehicle model training, mining, labeling, and replay; no direct AI model development is specified.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 6, 2026 (UTC)