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Remote Autonomous Driving Engineer Jobs in California

Waabi

Research Engineer, Calibration

San Francisco, CA · On-site +1

$158K - $269K/yr

To learn more visit: www.waabi.ai As a Research Engineer in Calibration, you will create the next generation of calibration systems autonomous driving. You will collaborate with our team of world ...

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Waabi

Research Engineer, Calibration

San Francisco, CA · On-site +1

$158K - $269K/yr

To learn more visit: www.waabi.ai As a Research Engineer in Calibration, you will create the next generation of calibration systems autonomous driving. You will collaborate with our team of world ...

Uber

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 Software Engineer, you will be at the ...

Uber

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 Staff Software Engineer , you will be at the ...

Uber

Autonomy is now a data race-and Uber has an edge: We collect rare, real-world driving data at a ... Partner with platform, product, and security engineering teams to enable the successful deployment ...

Uber

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 ...

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All JobsRemote Autonomous Driving Engineer JobsRemote Autonomous Driving Engineer Jobs in California

Remote Autonomous Driving Engineer information

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 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 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.

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 most commonly searched types of Autonomous Driving Engineer jobs in California? The most popular types of Autonomous Driving Engineer jobs in California are:
What are popular job titles related to Remote Autonomous Driving Engineer jobs in California? For Remote Autonomous Driving Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Autonomous Driving Engineer jobs in California look for? The top searched job categories for Remote Autonomous Driving Engineer jobs in California are:
What cities in California are hiring for Remote Autonomous Driving Engineer jobs? Cities in California with the most Remote Autonomous Driving Engineer job openings:
Remote Autonomous Driving Engineer jobs near you
Principal Engineer, Autonomy

Principal Engineer, Autonomy

AeroVect

South San Francisco, CA • On-site, Remote

$300K - $350K/yr

Full-time

Posted 18 hours ago

Job description

Who We Are
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world's largest airlines and ground handling providers. For more information, visit www.aerovect.com.
We are hiring a Principal Engineer for Autonomy - the senior-most individual contributor in our autonomy organization. You will have the deepest hands-on technical ownership of one or more of Perception, Prediction, and Planning, with cross-stack influence across the rest of the autonomy stack. You will report directly to the VP of Engineering, with no direct reports of your own, but with the expectation that you set technical direction the rest of the autonomy team follows.
We are looking for someone who is excellent both at the systems level and at execution - a senior IC with the technical depth to anchor the hardest decisions in autonomy and the bias for shipping to convert those decisions into running code on a vehicle.
You Will
You are the senior-most IC in autonomy, with the deepest technical ownership of either Perception, Prediction, or Planning (or any combination thereof) and influence across the rest of the stack.
  • Perception. Own the design and evolution of the perception stack - detection, classification, tracking, and multi-modal sensor fusion across the available modalities. Drive perception robustness across the long tail of real-world operating conditions, and set the direction for where and how deep learning is best applied across the perception pipeline.
  • Prediction. Own the prediction stack and the design of models for intent inference, behavior forecasting, and handling occlusions and edge cases. Set the direction for how prediction integrates with perception upstream and planning downstream.
  • Planning. Own the design of the planning and decision-making stack, from structured driving behaviors to the domain-specific maneuvers required for autonomous GSE operations. Set the direction for where learned components earn their place in the planner.
  • Cross-stack influence. Set the technical direction at the interfaces between your primary areas and the rest of the stack, and partner with the other senior engineers in autonomy to keep the system coherent end-to-end.
  • Autonomy architecture. Own the functional and SW architecture of the autonomy stack, and partner with neighboring teams towards its implementation.

You Have
  • 15+ years of hands-on experience building production autonomy systems, with strong technical depth across multiple modules (localization, perception, prediction, planning, controls). You think at the level of the autonomy system, not a single module.
  • Demonstrated track record of shipping autonomy components that have run in production on real vehicles at non-trivial scale - not just research prototypes or simulation results.
  • Prior experience as the most senior individual contributor in an autonomy organization - setting direction, mentoring staff/senior engineers, and partnering with engineering leadership without managing a team yourself.
  • Deepest technical depth in perception, prediction, or planning (ideally more than one of the three).
  • Strong software engineering fundamentals in C++ and Python. You write or review code that other senior engineers want to extend and trust in a safety-relevant system.
  • Fluency with modern deep learning for autonomy, including the practical realities of training, evaluation, deployment, and lifecycle management of models that have to work in the real world.
  • Experience working in or with ROS / ROS 2 and the distributed-systems realities of on-vehicle compute (real-time constraints, IPC, fault containment).
  • A bias for execution. You ship. You close out problems. You convert ambiguity into a plan and the plan into running code on a vehicle.

We Prefer
  • Experience with safety-critical or functional-safety-relevant systems (ISO 26262, ISO 13849, SOTIF, or aerospace equivalents).
  • Experience operating in an Operational Design Domain that involves heavy interaction with humans, mixed traffic, or unstructured environments.
  • Familiarity with simulation-driven verification and the use of simulation as part of a CI/CD pipeline for autonomy.

Why this role at AeroVect?
  • A real ODD with real constraints. Airports are one of the few environments where commercial autonomy is genuinely viable today and where the path to removing the safety driver is concrete rather than speculative.
  • Scope. This is the senior autonomy IC role at AeroVect. You are the senior-most technical voice across Perception, Prediction, and Planning, with cross-stack influence across the rest of the autonomy stack.
  • A defined path to scale, not a science project. A real commercial deployment with a concrete path to removing the safety driver and scaling the fleet. Your work has a destination.

Apply