Perception for autonomous vehicles (AV) is one of the most exciting and challenging areas to work on today. Machine learning plays a crucial role in this field, but to excel in machine learning for Perception AV, we need to master the fundamentals. Join the Perception ML Foundation team, where we combine expertise in machine learning, high-performance computing (HPC), and cloud computing to build an efficient and scalable perception *ML factory*. This factory streamlines the generation of perception ML models, making the process efficient, scalable, reproducible and user-friendly. It encompasses major ML workflows, including data preparation, deep neural network (DNN) training, production optimization, and large-scale cloud inference and evaluation.We believe that creating this high-throughput factory requires diverse, interdisciplinary thinking and expertise. This includes understanding modern Perception architectures, efficient ML techniques, large-scale software system design, HPC, accelerated-cloud compute hardware (GPUs), MLOps, and micro-services. We refer to all these abilities as ML foundation engineering.

What You’ll Be Doing:

• Serve as a technical leader on our most demanding, cross-functional projects.

• Enhance our DNN training code to improve training speed, scalability, and resource efficiency.

• Design training code that supports simultaneous use by multiple engineers and tasks.

• Design and implement a horizontally scalable, high-throughput cloud workloads such as inference and data-preparation pipeline for evaluation and KPI calculation.

• Streamline workflows to create verified, deployable artifacts from annotated data.

• Develop tools for introspection and visualization to identify areas for improvement.

• Collaborate closely with platform and perception DNN engineers, combining knowledge of large-scale ML systems with deep understanding of perception DNNs.

• Provide architectural guidance and detailed technical direction while nurturing a continuous delivery culture.

• Mentor and guide the career development of other engineers, fostering a collaborative and innovative environment.

What We Need to See:

• MSc or PhD in computer science or equivalent experience.

• 8+ years of related industry experience.

• Familiarity with modern machine learning environments such as PyTorch.

• Excellent programming skills in Python. CUDA and C++ are greatly appreciated

• Passion for software development and code quality, including writing unit tests and benchmarks.

• Strong optimization skills, from high-level ML algorithms to low-level hardware utilization.

• Ability to communicate clearly and collaborate effectively within and outside the team.

• Creativity, curiosity, proactivity, and thoroughness in problem-solving.

• Experience in providing technical guidance and leadership across multiple teams.

Ways to Stand Out From the Crowd:

• Publications in the area of efficient ML (accelerating training and inference).

• Industry experience in building large-scale ML pipelines, possibly for autonomous vehicles.

• Significant contributions to leading related open-source projects.

NVIDIA has some of the most forward-thinking and hardworking people in the world. If you’re creative and autonomous, we want to hear from you!

#LI-Hybrid

The base salary range is 272,000 USD - 419,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.