Senior Machine Learning Engineer, Prediction - Autonomous Driving

NVIDIA•Santa Clara, CA

8d•$224,000 - $356,500

About The Position

NVIDIA is seeking a Senior Engineer to develop and productize autonomous driving solutions as part of its prediction team. The role focuses on prediction modules that produce multimodal, scene-consistent predictions for other road participants, improving robustness, accuracy, and efficiency to support autonomous driving across varied environments. The engineer will design end-to-end prediction and autonomous-driving-stack solutions using state-of-the-art machine learning, conduct applied research and develop deep learning models, and create approaches that generalize across operational design domains and regions. The role also involves data-driven development with data collection and labeling teams, using simulation and augmentation for extreme scenarios, and productizing solutions that meet safety, latency, and software robustness requirements.

Requirements

PhD with 6 or more years, master's degree with 10 or more years, or bachelor's degree (or equivalent experience) with 12 or more years of meaningful experience in computer science, computer engineering, or a related technical field.
Hands-on experience developing deep learning and algorithms to solve sophisticated real-world problems.
Proficiency with deep learning frameworks such as PyTorch.
Experience in data-driven development and collaboration with data and ground-truth teams.
Strong programming skills in Python and/or C++.
Outstanding communication and teamwork skills.

Nice To Haves

Proven expertise developing generalizable machine-learning solutions for autonomous driving or robotics.
Hands-on experience developing and deploying DNN-based solutions to embedded platforms for real-time applications.
Proven deep-learning expertise supported by technical publications in leading conferences or journals.
Expertise with Transformers, BEV architectures, or end-to-end machine-learning systems.
More than two years of technical leadership experience involving significant technical and organizational challenges.

Responsibilities

Design end-to-end prediction and autonomous-driving-stack solutions using state-of-the-art machine learning for varied driving environments.
Conduct applied research and develop innovative deep learning models, including end-to-end models.
Develop generalizable approaches that support diverse operational design domains and expansion across countries and regions.
Drive and prioritize data-driven development with data collection and labeling teams, including planning and prioritizing data collection and labeling and optimizing labeling efficiency.
Use data simulation and augmentation to address extreme scenarios.
Productize developed solutions to meet safety, latency, and software robustness requirements.