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Full Time Autonomous Driving Engineer Jobs (NOW HIRING)

Motional

Autonomous Driving Test Operator

Pittsburgh, PA

$17.75 - $21.75/hr

We are hiring Autonomous Driving Test Operators to support Motional's growing AV Test Operations ... As an AV Test Operator, you will serve as the "eyes and ears" for engineering teams by safely ...

Motional

Autonomous Driving Test Operator

Pittsburgh, PA · On-site

$17.75 - $21.75/hr

We are hiring Autonomous Driving Test Operators to support Motional's growing AV Test Operations ... As an AV Test Operator, you will serve as the "eyes and ears" for engineering teams by safely ...

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All JobsFull Time Autonomous Driving Engineer Jobs

Full Time Autonomous Driving Engineer information

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$59K

$137.3K

$196.5K

How much do full time autonomous driving engineer jobs pay per year?

As of Jun 29, 2026, the average yearly pay for full time 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 are the key skills and qualifications needed to thrive as a Full Time Autonomous Driving Engineer, and why are they important?

To thrive as a Full Time Autonomous Driving Engineer, you need strong expertise in computer science, robotics, and machine learning, typically supported by a degree in engineering or a related field. Familiarity with tools like ROS (Robot Operating System), C++, Python, and experience with sensor fusion, perception algorithms, and autonomous vehicle simulation systems is essential. Strong problem-solving skills, teamwork, and effective communication are crucial soft skills for success in this role. These skills ensure the development of safe, reliable, and innovative autonomous driving systems in a rapidly evolving industry.

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

AspectFull Time Autonomous Driving EngineerAutonomous Vehicle Software Engineer
Required CredentialsBachelor's or Master's in Computer Science, Robotics, or Electrical Engineering; experience in autonomous systemsSimilar credentials; focus on software development for autonomous systems
Work EnvironmentResearch labs, automotive companies, tech firms working on autonomous vehiclesSoftware development teams, automotive or tech companies, often in collaborative environments
Industry UsageUsed broadly in autonomous vehicle development projectsPrimarily in software development for autonomous systems within automotive industry

Both roles require similar educational backgrounds and work environments, focusing on autonomous vehicle technology. The main difference lies in scope: Full Time Autonomous Driving Engineers often oversee entire systems, while Autonomous Vehicle Software Engineers focus specifically on software components.

What are some of the main challenges faced by Full Time Autonomous Driving Engineers in ensuring the safety and reliability of self-driving systems?

Full Time Autonomous Driving Engineers often encounter challenges related to ensuring the safety and reliability of autonomous vehicles in unpredictable real-world conditions. This involves integrating complex sensor data, handling edge cases that are rare but critical, and maintaining robust testing and validation processes. Engineers must also collaborate closely with software, hardware, and testing teams to address issues like sensor calibration, perception errors, and decision-making logic. Staying updated with regulatory standards and adapting systems to new environments are additional ongoing challenges in this rapidly evolving field.

What does a Full Time Autonomous Driving Engineer do?

A Full Time Autonomous Driving Engineer designs, develops, and tests systems that enable vehicles to drive themselves safely and efficiently. Their work often involves integrating sensors, creating algorithms for perception and decision-making, and collaborating with multidisciplinary teams to ensure system reliability. They may also work on simulation, data analysis, and software updates to improve autonomous functionalities and comply with safety standards. The role requires strong skills in programming, robotics, and machine learning, as well as a deep understanding of automotive technologies.
More about Full Time Autonomous Driving Engineer jobs
What are the most commonly searched types of Autonomous Driving Engineer jobs? The most popular types of Autonomous Driving Engineer jobs are:
What job categories do people searching Full Time Autonomous Driving Engineer jobs look for? The top searched job categories for Full Time Autonomous Driving Engineer jobs are:
Full Time Autonomous Driving Engineer jobs near you
Infographic showing various Full Time Autonomous Driving Engineer job openings in the United States as of June 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $137,309 per year, or $66 per hour.

Senior Software Engineer - Autonomous Driving

NVIDIA AI

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 3 days ago

Job description

Job Summary:
NVIDIA AI is building the software foundation for scalable, high-performance vehicle computing platforms that power autonomous driving and centralized vehicle architectures. They are seeking a Senior Software Engineer to lead architecture and optimization efforts across the autonomous driving software stack, focusing on deep neural network optimization and deployment on NVIDIA automotive compute platforms.
Responsibilities:
• Lead architecture and technical strategy for optimizing inference workloads in autonomous driving applications.
• Drive end-to-end performance analysis across DNN models, TensorRT/compiler flows, CUDA kernels, memory behavior, scheduling, runtime services, and automotive platform constraints.
• Develop and guide model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, kernel selection, and layout/memory optimization.
• Collaborate with TensorRT, CUDA, compiler, silicon architecture, perception, planning, DriveOS and safety platform teams.
• Build tools, methodologies, and metrics for profiling, benchmarking, debugging, and validating model and platform performance.
Qualifications:
Required:
• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 12+ years of software engineering experience in systems software, AI/ML infrastructure, deep learning inference, compiler/runtime technology, or platform performance.
• Strong C/C++ and practical Python experience.
• Deep familiarity with TensorRT, TensorRT-LLM, ONNX, PyTorch, CUDA, Triton, or related frameworks.
• Experience optimizing DNN models for latency, throughput, memory footprint, and power.
Preferred:
• Hands-on experience with TensorRT internals, CUDA kernels, Triton kernels, or other compiler/runtime technologies.
• Experience deploying optimized DNNs, LLMs, VLMs, or perception models on embedded, edge, robotics, or automotive platforms.
• Background in autonomous driving, ADAS, robotics, real-time systems, safety-aware software, or deterministic low-latency systems.
• Experience with ISO 26262, QNX, Safe RTOS, DriveOS, Linux, hypervisors, or virtualization.
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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