Staff Software Engineer, Deep Learning Acceleration

Aurora; Philadelphia (Philadelphia County); Hybrid; USD 171,000 - 274,000; Full time

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

Aurora is seeking a Senior Staff Software Engineer focused on Deep Learning Acceleration to enhance DL networks used in our autonomous vehicle systems. You will analyze performance, optimize software architecture and latency, and deploy DL models on AVs and data centers.

Ideal candidates have 5+ years in software engineering with strong CUDA/C++, Python, and experience in DL frameworks like PyTorch or TensorFlow; familiarity with profiling tools and a hybrid work model is preferred.

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, specializing in optimizing workloads to reduce GPU memory usage, minimize latency, and/or maximize throughput.
• Proficiency in 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 PyTorch or TensorFlow, ensuring efficient and scalable model deployment.
• Strong understanding of computer vision and transformer-based DL architectures.
• Strong analytical skills for diagnosing and troubleshooting performance bottlenecks.
• Ability to quickly learn and adapt to emerging technologies; experience with large code bases.

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.

Skills

CUDA

C++

Python

GPU optimization

Roofline model

Deep learning frameworks

Linux

Performance analysis

Education

BS/MS/PhD in Computer Science or related field

Tools

NVIDIA Nsight Systems

NVIDIA Nsight Compute

TensorRT

OpenAI Triton

Mojo

PyTorch

TensorFlow

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.

Senior Staff Software Engineer – Deep Learning Acceleration

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 evolving. Strong communication skills are essential, as you will be working in a fast-paced environment with large code bases and collaborating with cross-functional teams.

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, 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.

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.

Base Salary

For roles based in Mountain View, CA and San Francisco, CA: The salary range for this position is $189,000 - $274,000 per year.

For roles based in Pittsburgh, PA: The salary range for this position is $171,000 - $247,000 per year.

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.

Working at Aurora

At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks. We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week. Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom.

Our Commitment to Safety

At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization’s long-term success by prioritizing working safely, no matter what.

Our Commitment to Inclusion

Aurora considers candidates without regard to their race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, pregnancy status, parent or caregiver status, ancestry, political affiliation, veteran and/or military status, physical or mental disability, or any other status protected by federal or state law. Aurora considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at . For California applicants, information collected and processed as part of your application and any job applications you choose to submit is subject to Aurora’s California Employment Privacy Policy.