Senior Machine Learning Engineer, Prediction - Autonomous Driving

NVIDIA•Santa Clara, CA

1d•$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 prediction and autonomous-driving-stack solutions using state-of-the-art machine-learning techniques, conduct applied research and development on deep-learning models, and develop approaches that generalize across operational design domains and geographic regions. The role also emphasizes data-driven development with data collection and labeling teams, using simulation and augmentation to address extreme scenarios, and productizing solutions to meet safety, latency, and software-robustness requirements.

Requirements

PhD with 6 or more years, MS with 10 or more years, or BS (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++.
Strong 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 2 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 techniques for diverse driving environments.
Conduct applied research and develop innovative deep-learning models, including end-to-end models.
Develop generalizable approaches to support diverse operational design domains and country or regional expansion.
Prioritize data-driven development in collaboration with data collection and labeling teams, including planning and prioritizing data collection and labeling and improving labeling efficiency.
Leverage data simulation and augmentation to solve extreme scenarios.
Productize developed solutions to meet safety, latency, and software-robustness requirements.