Staff Software Engineer, Deep Learning Acceleration

Who We Are – Aurora’s mission is to deliver the benefits of self‑driving technology safely, quickly, and broadly. The Aurora Driver will create a new era in mobility and logistics, bringing a safer, more efficient, and more accessible future to everyone. Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that makes our roads safer, gets crucial goods where they need to go, and makes mobility more efficient and accessible for all.

About the role

As a Staff Software Engineer focusing on Deep Learning Acceleration, you will enhance the performance of deep‑learning networks used in Aurora’s Autonomous Vehicle (AV) systems. You will conduct thorough performance analysis and optimization of these networks, ensuring efficient operation both onboard the vehicle and during training on large‑scale data centers. The role requires deep expertise in software architecture, system performance, and latency, and involves close collaboration with engineers and researchers to improve the efficiency and reliability of self‑driving technology.

Responsibilities

• Conduct performance analysis and optimization of deep‑learning networks running on the Autonomous Vehicle (AV).
• Optimize software architecture, system performance, and latency for deep‑learning applications.
• Work on deployment of deep‑learning models on the AV and training on large‑scale data centers.
• Troubleshoot performance issues using profiling and roofline model techniques.
• Collaborate with cross‑functional teams to enhance the efficiency of self‑driving technology.

Required Qualifications

• Minimum 5+ years of professional experience in software engineering.
• BS, MS, or PhD in Computer Science or a related field.
• Strong programming skills in CUDA, C++ and Python.
• Extensive experience in high‑performance computing and parallel programming, focusing on reducing GPU memory usage, minimizing latency, and/or maximizing throughput.
• Proficiency with performance analysis tools such as NVIDIA Nsight Systems, Nsight Compute, and applying roofline model techniques.
• Hands‑on experience optimizing DL/ML workloads at the framework level using at least one deep‑learning framework (e.g., PyTorch, TensorFlow).
• Strong understanding of computer‑vision fundamentals and transformer‑based deep‑learning architectures.
• Analytical skills for diagnosing and troubleshooting performance bottlenecks in complex systems.
• Ability to quickly learn and adapt to emerging technologies in a fast‑paced environment.
• Experience working on large code bases in a fast‑growing environment.
• Strong communication skills for effective teamwork across multidisciplinary teams.
• Comfortable working in Linux/Unix environments.

Desirable Qualifications

• Hands‑on experience in motion planning or related fields such as robotics, autonomous systems, systems software, or computer vision.
• Experience with TensorRT, OpenAI Triton, Mojo, and other inference acceleration tools.

Pay

For roles based in Mountain View, CA and San Francisco, CA: $189,000 – $274,000 per year.
For roles based in Pittsburgh, PA: $171,000 – $247,000 per year.
Aurora’s pay ranges are determined by role, level, and location. Within the range, the starting base pay will be set based on skills, experience, qualifications, education, and market conditions. The successful candidate will also be eligible for an annual bonus, equity compensation, and additional benefits.

Benefits

Annual bonus, equity compensation, and a comprehensive benefits package.

Schedule

Aurora operates a hybrid work environment; employees are expected to be in the office at least three days per week.