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Remote Autonomous Driving Engineer Jobs (NOW HIRING)

AeroVect

Infrastructure Engineer

South San Francisco, CA · On-site +1

$129K - $169K/yr

If you have a passion for applying autonomous driving technologies to impact the flow of goods for millions of people, we want to talk to you! You will work closely with our engineering team across ...

General Motors

Principal AI/ML Engineer

$296K - $423K/yr

Trajectory generation is one of the most critical components of an autonomous driving system. Itis ... Remote/Hybrid: Thisrole is based remotely but if you live within a 50-mile radius of Austin ...

General Motors

Principal AI/ML Engineer

Sunnyvale, CA · On-site +1

$296K - $423K/yr

Trajectory generation is one of the most critical components of an autonomous driving system. Itis ... Remote/Hybrid: Thisrole is based remotely but if you live within a 50-mile radius of Austin ...

Motional

Principal Engineer

... autonomous driving technology, excited by intellectual challenges, and interested in pursuing ... Strong programming skills in C++ and/or CUDA programming

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$59K

$137.3K

$196.5K

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

As of Sep 6, 2026, the average yearly pay for remote autonomous driving engineer in the United States is $137,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $196,000.00 per year, depending on experience, location, and employer.

What is a remote autonomous driving engineer?

A Remote Autonomous Driving Engineer is a professional who designs, develops, tests, and implements software and systems that enable vehicles to operate without direct human control. These engineers often work remotely, using cloud-based tools and simulations to collaborate with teams and test autonomous driving algorithms. Their responsibilities may include sensor integration, perception modeling, path planning, and ensuring safety and compliance with industry standards. They play a key role in advancing self-driving technology by working on cutting-edge machine learning, computer vision, and robotics challenges.

What are the key skills and qualifications needed to thrive as a remote autonomous driving engineer, and why are they important?

To thrive as a Remote Autonomous Driving Engineer, you need a strong background in robotics, computer vision, machine learning, and programming languages like Python or C++, often backed by a degree in engineering or computer science. Experience with simulation tools (e.g., ROS, CARLA), real-time data processing, and knowledge of automotive safety standards or certifications such as ISO 26262 are typically required. Excellent problem-solving skills, remote communication abilities, and adaptability are crucial soft skills for collaborating with distributed teams and addressing complex challenges. These competencies ensure the safe and efficient development of reliable autonomous driving systems in a remote work environment.

What are the unique challenges of collaborating with global teams as a remote autonomous driving engineer?

As a Remote Autonomous Driving Engineer, you'll frequently collaborate with cross-functional teams spanning different time zones and regions. This can present challenges such as coordinating meetings, managing asynchronous communication, and ensuring clear documentation of technical requirements. To succeed, it's essential to develop strong written communication skills and utilize collaborative tools for version control, code review, and project management. Building relationships with colleagues remotely also requires proactive engagement and regular check-ins to maintain alignment on project goals.

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

AspectRemote Autonomous Driving EngineerRemote Autonomous Vehicle Software Developer
Required CredentialsEngineering degree, specialized in autonomous systems, certifications in robotics or AISoftware development background, experience with autonomous vehicle software, relevant certifications
Work EnvironmentCollaborates with hardware teams, field testing, simulation environmentsFocuses on coding, software testing, simulation, and integration
Industry UsageDesigns and tests autonomous driving systems, sensor integrationDevelops software components for autonomous vehicles, algorithms, and control systems

While both roles involve autonomous vehicle technology, the Remote Autonomous Driving Engineer focuses on system design, testing, and integration of autonomous driving systems, often working closely with hardware. The Remote Autonomous Vehicle Software Developer primarily concentrates on coding, software development, and simulation tasks within autonomous vehicle software platforms.

More about Remote Autonomous Driving Engineer jobs

What cities are hiring for Remote Autonomous Driving Engineer jobs?

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What are the most commonly searched types of Autonomous Driving Engineer jobs?

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What states have the most Remote Autonomous Driving Engineer jobs?

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What job categories do people searching Remote Autonomous Driving Engineer jobs look for?

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Remote Autonomous Driving Engineer jobs near you
Infographic showing various Remote Autonomous Driving Engineer job openings in the United States as of August 2026, with employment types broken down into 66% Full Time, 32% Part Time, and 2% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $137,309 per year, or $66 per hour.

Senior Machine Learning Engineer

Uber Technologies, Inc.

Sunnyvale, CA • On-site, Remote

Full-time

Retirement

Posted 10 days ago

Key responsibilities

  • Lead the development of algorithms to tackle complex urban environments, focusing on robustness and safety.

  • Implement end-to-end AI-driven methods for autonomy pipelines using large-scale real-world data.

  • Architect scalable machine learning systems, including management of upstream sensor dependencies.

Uber rating

6.7

Company rating: 6.7 out of 10

Based on 117 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire

Job description

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 is 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.

As a Senior ML Engineer, you will be at the forefront of Physical AI, developing core components of our Autonomous Driving stack. You will be responsible for the development and implementation of the latest machine learning techniques across the autonomy systems. The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar. You will collaborate with engineers across big data, compute, and cloud engineering to build platforms that harness scale and real-world complexity to reimagine how the world moves.

What the Candidate Will Do
  • Autonomous Driving Algorithm Development: Lead the development of algorithms to tackle complex urban environments, focusing on robustness and safety.
  • End-to-End AI Implementation: Implement end-to-end AI-driven state-of-the-art methods for autonomy pipelines, leveraging massive-scale real-world data.
  • Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies.
  • Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability.
  • Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling.
  • Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.
Basic Qualifications
  • 4+ years of working experience in the ML/Robotics industry.
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields.
  • Proficient in Python and Linux environments.
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).
Preferred Qualifications
  • Experience in the Autonomous Driving domain.
  • Proven track record of deploying ML models in safety-critical physical systems.
  • Master's or PhD degree in Computer Vision, Robotics, or Machine Learning.
  • Familiarity with C++ and high-performance computing.
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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.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 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.

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