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Director Autonomous Driving Engineer Jobs in Seattle, WA

Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact ... Experience in autonomous driving or ADAS is a plus -- background in perception pipelines, sensor ...

Deep Learning Engineer

Seattle, WA · On-site

$140K - $220K/yr

Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact ... Experience in autonomous driving or ADAS is a plus - background in perception pipelines, sensor ...

PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX provides a stable programming model and portable instruction set Architecture (ISA) for NVIDIA GPUs ...

Senior GPU Compiler Development Engineer

Redmond, WA · On-site

$137K - $180K/yr

PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX provides a stable programming model and portable instruction set Architecture (ISA) for NVIDIA GPUs ...

Senior AI Engineer

Redmond, WA · On-site +1

$117K - $160K/yr

About Job AI Engineer - Vision AI, Agentic Systems & Physical AI Location: Seattle / Palo Alto ... Experience with robotics, autonomous driving, simulation, digital twins, or embodied AI systems

New

Senior Software Engineer, Model Lifecycle

Kirkland, WA · Hybrid

$139K - $183K/yr

In this hybrid role, you will report to an engineering manager. You will: * Design, build, and ... Passionate about data-centric AI and autonomous driving applications We prefer: * Experience in ...

Senior Software Engineer, Build Infrastructure

Seattle, WA · On-site

$139K - $183K/yr

Every line of that autonomous driving software has to be compiled, tested, and validated reliably ... We are searching for a passionate engineer with a strong curiosity for optimizing build speeds and ...

... autonomous driving systems. Kenworth is committed to fostering an environment of diversity ... as directed. • Identifies, prioritizes, and coordinates resolution of production, production ...

... autonomous driving systems. Kenworth is committed to fostering an environment of diversity ... as directed. • Identifies, prioritizes, and coordinates resolution of production, production ...

Senior Electrical Design Engineer

Kirkland, WA · On-site

$118K - $159K/yr

... autonomous driving systems. Kenworth is committed to fostering an environment of diversity ... Prepares engineering activity status reports and other detailed reporting as directed. Identifies ...

... autonomous driving systems. Kenworth is committed to fostering an environment of diversity ... Prepares engineering activity status reports and other detailed reporting as directed. Identifies ...

Showing results 21-40

Director Autonomous Driving Engineer information

See Seattle, WA salary details

$83.1K

$221.6K

$289.1K

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

As of Sep 3, 2026, the average yearly pay for director autonomous driving engineer in Seattle, WA is $221,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $161,000.00 and $287,900.00 per year, depending on experience, location, and employer.

What does a director autonomous driving engineer do?

A Director Autonomous Driving Engineer leads and manages teams responsible for developing self-driving vehicle technologies. This role oversees the technical strategy, project execution, and integration of hardware and software for autonomous systems. Directors in this position collaborate closely with cross-functional teams, ensure safety and regulatory compliance, and drive innovation to advance autonomous vehicle capabilities. They also mentor engineers, set technical standards, and work with stakeholders to align product goals with business objectives.

What are the key skills and qualifications needed to thrive as a director autonomous driving engineer?

To thrive as a Director Autonomous Driving Engineer, you need deep expertise in robotics, computer vision, sensor fusion, and machine learning, typically supported by an advanced degree in engineering or computer science and significant industry experience. Familiarity with tools such as ROS, simulation platforms, automotive-grade software systems, and relevant safety certifications (like ISO 26262) is crucial. Strong leadership, strategic thinking, and effective communication are essential soft skills for guiding multidisciplinary teams and collaborating with stakeholders. These abilities are vital for driving innovation, ensuring technical excellence, and delivering safe, reliable autonomous driving solutions.

How does a director autonomous driving engineer typically collaborate with cross-functional teams within an organization?

As a Director of Autonomous Driving Engineering, you'll regularly collaborate with cross-functional teams such as hardware engineers, data scientists, product managers, safety and compliance experts, and user experience designers. Your role involves aligning the technical roadmap with business goals, ensuring seamless integration of software and hardware, and facilitating effective communication between departments. This collaborative approach is crucial for addressing complex challenges, maintaining project momentum, and ensuring the autonomous driving system meets safety, regulatory, and performance standards.

What is the difference between Director Autonomous Driving Engineer vs Senior Autonomous Driving Engineer?

AspectDirector Autonomous Driving EngineerSenior Autonomous Driving Engineer
ResponsibilitiesOversees autonomous driving projects, manages teams, sets strategic goalsDesigns and develops autonomous driving systems, implements algorithms
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsRelevant engineering degree, several years of experience in autonomous systems
Work EnvironmentLeadership roles in R&D teams, cross-department collaborationHands-on engineering in labs or development teams
Industry UsageCommon in tech and automotive companies for strategic rolesCommon in engineering teams focused on system development

The main difference is that the Director Autonomous Driving Engineer focuses on leadership, strategy, and project oversight, while the Senior Autonomous Driving Engineer is primarily involved in technical development and implementation. Both roles require relevant technical credentials, but the director position emphasizes management and strategic planning within autonomous driving projects.

What are popular job titles related to Director Autonomous Driving Engineer jobs in Seattle, WA?

For Director Autonomous Driving Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Director Autonomous Driving Engineer jobs in Seattle, WA look for?

The top searched job categories for Director Autonomous Driving Engineer jobs in Seattle, WA are:

Infographic showing various Director Autonomous Driving Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $221,584 per year, or $106.5 per hour.

Senior AI Inference Engineer - Model Optimization & Deployment

Zoox

Seattle, WA • On-site

$225K - $305K/yr

Full-time

Medical, Life, PTO

Re-posted 26 days ago


Zoox rating

7.8

Company rating: 7.8 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

212th of 496 rated machine equipment manufacturers


Job description

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.

As a Model Optimization & Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex models (LLMs, VLMs, or FMs) for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices.
In this role, you will:
  • Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA).
  • Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
  • Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries.
  • Develop and optimize custom ML OPs and TensorRT Plugins with efficient CUDA kernels to minimize latency and maximize memory bandwidth on AI accelerators.
  • Write production-level, low latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems.
Qualifications:
  • Deep expertise in model quantization (PTQ, QAT) and mixed-precision inference frameworks (INT8, FP8, FP4, BF16/FP16).
  • Proven experience optimizing large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs/VLAs) utilizing Efficient Attention mechanisms (e.g., FlashAttention, Linear Attention), KV-cache optimization (e.g., PagedAttention) and Speculative Decoding.
  • Extensive experience with model conversion/compilation pipelines (e.g., ONNX, TensorRT, torch.compile) and performing rigorous latency benchmark and model quality parity valuation.
  • Proficiency in low-level programming for AI accelerators, specifically developing and optimizing custom ML OPs and TensorRT Plugins with efficient CUDA kernel implementations.
  • Production-level C++ (14/17/20) and Python programming skills, with experience developing concurrent, memory-safe, real-time inference code for edge devices.
Bonus Qualifications:
  • Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection, BEV, 3D Occupancy Networks) and multi-modal sensor processing (Vision, LiDAR, Radar).
  • Experience with distributed training pipelines and model/tensor parallelism (PyTorch Distributed, Ray, DeepSpeed, Megatron-LM) and runtime efficiency optimization for GPU clusters.
  • Experience with end-to-end autonomous driving paradigms (VLM/VLA models, Foundation models) and edge deployment technologies (e.g., TensorRT-LLM).
$225,000 - $305,000 a year
Base Salary Range
 
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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About Zoox

Sourced by ZipRecruiter

Zoox is dedicated to creating the world's first fully autonomous vehicle fleet and the necessary ecosystem to make this technology accessible. Positioned at the crossroads of robotics, machine learning, and design, Zoox strives to deliver the future of mobility-as-a-service in urban settings. We seek exceptional individuals who share our enthusiasm and are eager to join a dynamic and results-driven team.

Industry

Manufacturing

Company size

1,001 - 5,000 Employees

Headquarters location

Foster City, CA, US