Senior Machine Learning Engineer, Prediction - Autonomous Driving

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Machine Learning EngineerData

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Requirements Summary

Minimum Requirement: PhD with 6+ years, MS with 10+ years, or BS (or equivalent experience) with 12+ years of meaningful experience in Computer Science, Computer Engineering,

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Machine Learning EngineerData

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.

We are now looking for an extraordinary Senior Engineer to develop and productize NVIDIA’s autonomous driving solutions. As a member of our prediction team, you will be driving solutions for prediction modules that are responsible for producing multi-modal scene consistent prediction for other road participants. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

Responsibilities

~1 min read

→Designing end-to-end solutions for Prediction and AV stack using state of the art ML techniques to enable agents prediction across various driving environments from complex intersections to rural curvy roads to multi-level highways.
→Applied research and development of innovative deep learning models, including end-to-end models
→Develop generalizable approaches to support diverse ODDs and Country/region expansion
→Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve prediction system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized
→Leverage data simulation and augmentation for solving extreme scenarios
→Productize the developed solutions by meeting product requirements for safety, latency, and SW robustness.

Requirements

~1 min read

Minimum Requirement: PhD with 6+ years, MS with 10+ years, or BS (or equivalent experience) with 12+ years of meaningful experience in Computer Science, Computer Engineering, or a related technical field.
Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., 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 as we work as a tightly-knit team, always discussing and learning from each other.

Proven expertise in developing generalizable ML solutions for autonomous driving or robotics.
Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.
Proven expertise in deep learning backed up by technical publications in leading conferences/journals.
Expertise with Transformers, BEV architectures, E2E ML systems.
Having over 2 years of experience in technical leadership involving significant technical and organizational challenges is highly advantageous.

Join us and help define the future of reliable, data-driven autonomous driving.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 20, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.