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Senior Machine Learning Engineer, Prediction – Autonomous Driving
NVIDIA. Design end-to-end solutions for Prediction and AV stack using state of the art ML techniques across diverse driving environments .
Posted 10/16/2026full-timeRemote • California • United StatesSenior💰 $224,000 - $356,500 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing deep learning models for autonomous driving applications, with a strong focus on data-driven development and collaboration with data teams. Proficient in leveraging advanced ML techniques and frameworks to create robust, generalizable solutions for diverse driving environments.
Highest-signal resume keywords
Deep Learning DevelopmentPython ProgrammingPyTorch FrameworkData-Driven DevelopmentDNN-Based Solutions
ATS Keywords
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Hard Skills
Deep LearningAlgorithms DevelopmentMachine Learning SolutionsData SimulationLabeling OptimizationTransformersBEV ArchitecturesE2E ML SystemsEmbedded PlatformsReal-Time Applications
Certifications & Qualifications
PhD in Computer ScienceMS in Computer EngineeringBS in Related Technical Field
Industry Keywords
Autonomous DrivingRoboticsData CollectionData LabelingSafety RequirementsLatency RequirementsSoftware Robustness
Tech Stack
Tools & technologiesPythonPyTorchC++
About the role
Key responsibilities & impact- Design end-to-end solutions for Prediction and AV stack using state of the art ML techniques across diverse driving environments
- Conduct 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 with data collection and labeling teams
- Prioritize data collection and labeling, and optimize labeling efficiency
- Leverage data simulation and augmentation for extreme scenarios
- Productize solutions to meet safety, latency, and software robustness requirements
Requirements
What you’ll need- 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
- 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++
- 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
Benefits
Comp & perks- Equity
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