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Staff Software Engineer, Deep Learning Acceleration

Pittsburgh, Pennsylvania💼 Full-time💰 $171,000–$171,000🗓 2026-06-03 → 2026-07-31

Core

Optimizing Deep Learning network performance for Autonomous Vehicle systems, focusing on reducing latency and maximizing throughput in both onboard execution and large-scale data center training.

Role type

Staff Software Engineer (Deep Learning Acceleration)

Builds

High-performance inference and training pipelines for self-driving software

Domain

Autonomous Vehicles / Deep Learning / High-Performance Computing

Deliverable

production ML models

Required skills

CUDA, C++, Python, high-performance computing, parallel programming, GPU memory optimization, latency reduction, profiling (NVIDIA Nsight Systems/Compute), roofline model analysis, PyTorch or TensorFlow, computer vision fundamentals, transformer architectures

Preferred skills

TensorRT, OpenAI Triton, Mojo, motion planning, robotics, systems software

Technologies

NVIDIA Nsight Systems, NVIDIA Nsight Compute, PyTorch, TensorFlow, Linux/Unix

Responsibilities

Conduct performance analysis and optimization of Deep Learning networks on AVs; Optimize software architecture and latency for deep learning applications; Deploy deep learning models on AVs and train on large-scale data centers; Troubleshoot performance issues using profiling and roofline model techniques; Collaborate with cross-functional teams to enhance self-driving technology efficiency

Seniority

Staff, hands-on IC

Rewrite
## 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. ## Requirements - 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, specializing in optimizing workloads to reduce GPU memory usage, minimize latency, and/or maximize throughput. - Proficiency in leveraging performance analysis tools such as NVIDIA Nsight Systems, Nsight Compute and applying techniques like roofline model for performance optimization. - Hands-on experience in optimizing DL/ML workloads at the framework level using at least one deep learning framework (e.g., PyTorch, TensorFlow), ensuring efficient and scalable model deployment. - Strong understanding of the fundamentals of computer vision and transformer-based deep learning architectures, with proficiency in foundational neural network building blocks. - Strong analytical skills for diagnosing and troubleshooting performance bottlenecks in complex systems. - Demonstrated ability to quickly learn and adapt to emerging technologies and tools in a fast-paced environment - Experience working on large code bases in a fast-growing environment. - Strong communication skills, enabling effective teamwork across multidisciplinary teams. - Comfortable working in Linux/Unix environments. ## Nice to Have - 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. ## Benefits The base salary range for this position is $171,000 - $247,000. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.
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