Senior Machine Learning Engineer, Prediction - Autonomous Driving

NVIDIA is hiring a Senior Machine Learning Engineer, Prediction - Autonomous Driving in Santa Clara, United States. It pays $224k-$357k a year and Level rates it ; you can apply on Level.

AI in this role

pytorch

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.

What You’ll Be Doing:

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.

What We Need to See:

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.

Ways to Stand Out from the Crowd:

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.

How we rate this

Senior Machine Learning Engineer, Prediction - Autonomous Driving at NVIDIA rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Senior Machine Learning Engineer, Prediction - Autonomous Driving is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $224k-$357k a year.
The role is based in US, CA, Santa Clara.
The job was posted on October 16, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorch

Also common in machine learning engineer jobs at this level

LLM TensorFlow AWS Generative AI Spark Fine-tuning

Pay

This job starts at: $224k
Typical machine learning engineer job: $198k

This posting starts 13% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

What's a project where you used PyTorch hands-on?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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