Aurora Innovation

Technology

StaffSoftwareEngineer,DeepLearningAcceleration

$250–400k ~AI est. Mountain View, California, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff Software Engineer, Deep Learning Acceleration at Aurora Innovation. Skills: Deep Learning Acceleration, Performance Optimization, Autonomous Vehicle Systems. Conduct performance analysis. Optimize Deep Learning networks”

Industry & Context.

Technology
Problems you'll solve

Analytical skills; Performance troubleshooting

What They're Looking For.

Must Have

5+ years of professional experience, BS, MS, or PhD in Computer Science, programming skills in CUDA, C++ and Python, high-performance computing experience, parallel programming experience, optimizing workloads to reduce GPU memory usage, optimizing workloads to minimize latency, optimizing workloads to maximize throughput, performance analysis tools proficiency, roofline model application, optimizing DL/ML workloads at framework level, understanding of computer vision fundamentals, understanding of transformer-based deep learning architectures, proficiency in foundational neural network building blocks, analytical skills for diagnosing performance bottlenecks, ability to quickly learn emerging technologies, experience working on large code bases, experience in a fast-growing environment, communication skills, Comfortable working in Linux/Unix environments

Nice to Have

Hands-on experience in motion planning, Experience with TensorRT, Experience with OpenAI Triton, Experience with Mojo, Experience with inference acceleration tools

What You'll Do.

Conduct performance analysis

Optimize Deep Learning networks

Optimize software architecture

Optimize system performance

Deploy deep learning models

Train on large-scale data centers

Troubleshoot performance issues

Apply profiling techniques

Apply roofline model techniques

Collaborate with cross-functional teams

Enhance efficiency of self-driving technology

How You'll Work.

Team & Collaboration

Cross-functional teams; Multidisciplinary teams

Communication Scope

Communication skills

Full Job Description

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, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn. Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. As a Staff Software Engineer focusing on Deep Learning Acceleration at Aurora, you will play a pivotal role in enhancing the performance of Deep Learning networks utilized in our Autonomous Vehicle (AV) systems. Your primary responsibility will be to conduct thorough performance analysis and optimization of these networks, ensuring they operate efficiently both onboard the vehicle and during training on large-scale data centers. This position requires a deep understanding of software architecture, system performance, and latency issues, as you will be tackling various challenges that arise in these areas. You will collaborate with a team of talented engineers and researchers to develop solutions that improve the overall efficiency and reliability of our self-driving technology. Your work will directly contribute to making transportation safer and more accessible. The role demands a strong analytical mindset, particularly in performance troubleshooting, where you will utilize techniques such as profiling and the roofline model to identify bottlenecks and optimize performance. In addition to your technical skills, you will need to be adaptable and quick to learn new technologies, as the field of deep learning and autonomous systems is rapidly

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