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Director Autonomous Driving Engineer Jobs in Texas

Bot Auto

GPU Engineer

Houston, TX · On-site

You would collaborate with software engineers, AI researchers, and hardware specialists to develop ... Optimize end-to-end GPU performance for real-time autonomous driving workloads , including sensor ...

Avride

Autonomous Vehicle Rideshare Drivers

Dallas, TX · On-site

$25/hr

We work closely with engineers and QA teams to bring cutting-edge technology safely to the real ... If you're passionate about driving, technology, and being part of an industry that's transforming ...

Avride

Be Seen First

Autonomous Vehicle Rideshare Driver

Dallas, TX · On-site

$25/hr

You'll experience autonomous driving technology firsthand while helping our team improve how these ... Interact professionally with riders, engineers, and company operations leaders to provide feedback ...

Avride

Autonomous Vehicle Rideshare Drivers

Dallas, TX · On-site

$25/hr

You'll experience autonomous driving technology firsthand while helping our team improve how these ... Interact professionally with riders, engineers, and company operations leaders to provide feedback ...

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Director Autonomous Driving Engineer information

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.

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Cities in Texas with the most Director Autonomous Driving Engineer job openings:

Director Autonomous Driving Engineer jobs near you

GPU Engineer

Bot Auto

Houston, TX • On-site

Full-time

Re-posted 3 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
You would collaborate with software engineers, AI researchers, and hardware specialists to develop high-performance solutions that meet the stringent requirements of autonomous driving applications. This is an exciting opportunity to work on next-generation transportation technology and make a meaningful impact on the future of mobility.
Key Responsibilities
  • Optimize end-to-end GPU performance for real-time autonomous driving workloads, including sensor processing (e.g., camera, LiDAR) and neural network inference.
  • Develop and optimize parallel computing algorithms and GPU-accelerated components using technologies such as CUDA.
  • Collaborate with cross-functional teams to design and improve onboard GPU software architectures that meet the computational requirements of perception, planning, and control modules.
  • Profile and analyze bottlenecks across GPU computation, memory access, data movement, synchronization, and CPU-GPU interaction.
  • Debug and optimize GPU-based software to improve latency, throughput, resource utilization, and runtime stability on embedded platforms.
Qualifications:
Required:
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
  • Strong knowledge of parallel computing principles, GPU architecture, memory hierarchy, and performance optimization techniques.
  • Experience profiling GPU applications using tools such as NVIDIA Nsight Systems, Nsight Compute, or equivalent tools.
  • Experience deploying or optimizing neural network inference workloads using technologies such as PyTorch, ONNX, and TensorRT.
  • Experience with real-time embedded systems and handling large data streams from sensors (camera, LiDAR, radar).
  • Strong proficiency in C/C++ and Python.

Preferred:
  • 3+ years of experience in GPU programming and optimization (e.g., CUDA, OpenCL, Vulkan).
  • Experience with NVIDIA Jetson Thor, NVIDIA DRIVE Thor, or similar embedded GPU platforms.
  • Experience with model quantization, including FP8 and NVFP4.
  • Experience managing concurrent GPU workloads and resource isolation using technologies such as NVIDIA Multi-Process Service (MPS), Multi-Instance GPU (MIG), or other related technologies.
  • Experience with GPU-accelerated sensor data compression, including camera, LiDAR, or other onboard sensor data.

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