ZipRecruiter

Log In

1

Autonomous Driving System Engineer Jobs in Austin, TX

Avride

Software Engineer - ML Platform

Austin, TX

... autonomous driving. We sit between Cloud Platform and ML engineers, turning low-level compute ... Solid Linux and systems debugging skills: performance investigation, networking, storage/IO

KRUSH Tech Inc

Lead Electronics Systems Engineer

Austin, TX ยท On-site

$120 - $160/hr

... autonomous systems. We're launching our U.S. operations from the ground up -- and this is a rare ... This role owns electrical system architecture, guides multidisciplinary hardware development, and ...

Nvidia

Senior GPU Compiler Development Engineer

Austin, TX ยท On-site

$121K - $160K/yr

We are looking for experienced Systems SW Compiler Engineers for an exciting role in our PTX ... PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX ...

Socket.dev

Senior Fullstack/Frontend Engineer

Austin, TX ยท On-site

$144.70 - $261.30/hr

Our team is developing national-scale, next-generation mapping systems from the ground up ... autonomous driving. You'll collaborate closely with product managers, backend engineers, machine ...

KRUSH Tech Inc

Lead UAS Systems Engineer

Austin, TX ยท On-site

$120 - $180/hr

... autonomous systems. We're launching our U.S. operations from the ground up -- and this is a rare ... This role owns the overall system architecture and leads cross-functional engineering teams through ...

Avride

Software Engineer - ML Platform

Austin, TX ยท On-site

... autonomous driving. We sit between Cloud Platform and ML engineers, turning low-level compute ... Solid Linux and systems debugging skills: performance investigation, networking, storage/IO

Last Energy

Thermofluids Engineer

Austin, TX ยท On-site

Lead the conceptual design, analysis, and execution of critical thermal system components and loops ... Operate autonomously , driving projects from concept to analysis and final design verification in a ...

Last Energy

Thermofluids Engineer

Austin, TX ยท On-site

Lead the conceptual design, analysis, and execution of critical thermal system components and loops ... Operate autonomously , driving projects from concept to analysis and final design verification in a ...

previous page

Showing results 41-60

All JobsAutonomous Driving System Engineer JobsAutonomous Driving System Engineer Jobs in Austin, TX

Autonomous Driving System Engineer information

See Austin, TX salary details

$53K

$126.1K

$165.5K

How much do autonomous driving system engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for autonomous driving system engineer in Austin, TX is $126,097.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,100.00 and $155,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an autonomous driving system engineer?

To thrive as an Autonomous Driving System Engineer, you need a strong background in computer science, robotics, or electrical engineering, with expertise in algorithms, perception, and control systems. Familiarity with technical tools such as ROS (Robot Operating System), Python/C++, sensor fusion frameworks, and experience with simulation platforms or automotive standards like ISO 26262 is typically required. Strong problem-solving abilities, effective teamwork, and clear communication distinguish top performers in this field. These skills ensure the safe, reliable, and innovative development of autonomous vehicle technologies in a rapidly evolving industry.

How do autonomous driving system engineers typically collaborate with cross-functional teams during the development process?

Autonomous Driving System Engineers frequently work alongside specialists in hardware, software, perception, mapping, and vehicle integration. Collaboration is essential, as engineers must coordinate with sensor experts, AI developers, and safety teams to ensure all system components function reliably together. Regular meetings, integration testing sessions, and shared development platforms are common to keep everyone aligned. This collaborative environment fosters innovation and ensures that system updates and new features are rigorously tested before deployment.

What does an autonomous driving system engineer do?

An Autonomous Driving System Engineer is responsible for designing, developing, and testing the software and hardware systems that enable vehicles to drive themselves. They work on integrating sensors, such as cameras and lidar, with algorithms for perception, localization, planning, and control to ensure safe and reliable autonomous operation. These engineers collaborate with multidisciplinary teams to validate system performance, address safety concerns, and continually improve the technology. Their work is crucial in advancing self-driving vehicles from prototypes to real-world deployment.

What is the difference between Autonomous Driving System Engineer vs Autonomous Vehicle Software Engineer?

AspectAutonomous Driving System EngineerAutonomous Vehicle Software Engineer
CredentialsBachelor's or Master's in Robotics, Computer Science, or Electrical Engineering; experience with sensor integration and control systemsBachelor's or Master's in Software Engineering, Computer Science; focus on software development and algorithms
Work EnvironmentResearch labs, automotive companies, tech firms working on autonomous systemsSoftware development teams within automotive or tech companies
Industry UsageDesigning and integrating autonomous driving systems and hardwareDeveloping software components for autonomous vehicles

The Autonomous Driving System Engineer focuses on integrating hardware and developing control systems for autonomous vehicles, while the Autonomous Vehicle Software Engineer primarily develops software algorithms and applications. Both roles often collaborate but differ in their core responsibilities and skill sets.

Autonomous Driving System Engineer jobs near you
Infographic showing various Autonomous Driving System Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $126,097 per year, or $60.6 per hour.

Software Engineer - ML Platform

Avride

Austin, TX

Full-time

Re-posted 9 days ago

Job description

About the team

The ML Platform team at Avride builds the infrastructure that powers large-scale ML training and data processing for autonomous driving. We sit between Cloud Platform and ML engineers, turning low-level compute, storage, and networking primitives into an ML platform that teams actually use - scalable orchestration, distributed compute, and production-grade tooling for the full model lifecycle.

About the role

As an ML Platform Engineer at Avride, you'll own critical pieces of the ML stack: workflow orchestration, distributed execution, resource governance, performance.You will shape how ML teams across the company run experiments and train models at scale. You will build the abstractions and services that make training workloads reliable, cost-efficient, and fast, helping ML teams run at scale on Kubernetes with strong reliability and excellent developer experience.

What you will do
  • Build and scale our ML compute platform on Kubernetes, using Argo Workflows for training, evaluation, and data processing orchestration
  • Design and implement core platform capabilities, including a Ray-based internal SDK for distributed execution, and multi-tenant resource governance - scheduling, priorities, quotas, and policy enforcement across GPU, CPU, memory, and IO
  • Improve end-to-end training throughput and platform efficiency by optimizing data access patterns, caching, and removing bottlenecks in storage, network, and resource contention
  • Work directly with ML teams to debug complex workload issues, drive root-cause analysis, and turn recurring problems into platform-level fixes
  • Evaluate, integrate and extend open-source tooling (Argo Workflows, Ray, Kubernetes ecosystem) to meet evolving platform needs
What you will need
  • Strong proficiency in Python or Go; C++ is a plus
  • Track record of designing and building scalable, maintainable systems and services
  • Experience operating production services end-to-end: APIs, reliability practices, observability
  • Deep knowledge of Kubernetes: how scheduling, resource management, controllers, and pod lifecycle actually behave under pressure
  • Solid Linux and systems debugging skills: performance investigation, networking, storage/IO
  • Ability to troubleshoot complex production issues across logs, metrics, and traces and drive them to resolution
Nice to have
  • Experience with Argo Workflows, Ray, MLflow, or comparable distributed ML tooling
  • Hands-on experience building or operating large-scale ML training systems: GPU scheduling, distributed training, training data pipelines
  • Track record of optimizing resource usage and performance in distributed environments

Apply