Staff Software Engineer, Deep Learning Acceleration

Job description

Job 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.

Job 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.