Machine Learning Engineer, End-to-End Autonomous Driving

We are seeking a Senior Machine Learning Engineer to join our end-to-end autonomous driving team! You will help build, train, and deploy large-scale E2E driving models that leverage VLM/VLA architectures, and build a data flywheel that continuously improves our systems in the real world! Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What you’ll be doing:

• Designing, implementing, and training large-scale end-to-end driving models.
• Driving the data flywheel: identifying failure cases, specifying data collection and labeling needs, and iterating models to close real-world performance gaps.
• Building, curating, and maintaining high-quality multimodal datasets (e.g., video, sensor, language/action traces) tailored for end-to-end autonomous driving.
• Developing and applying data-centric learning algorithms such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised methods.
• Exploring and productizing new data sources including simulation, synthetic data, and world-model-based generation/augmentation to improve coverage and robustness.
• Designing and implementing agentic data workflows that automate data discovery, labeling, evaluation, and retraining to maximize development velocity.
• Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.

• PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field
• Strong background in modern deep learning, including transformer-based architectures, video modeling, and multimodal VLM/VLA or foundation models.
• Hands-on experience training and deploying deep learning models on real-world datasets: data preprocessing, distributed training, evaluation, debugging, and iterative improvement.
• Practical experience with at least some data-centric methods such as active learning, curriculum learning, outlier/novelty detection, or large-scale sample mining.
• Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX), plus solid software engineering practices (testing, code review, CI/CD).
• Demonstrated ability to collaborate effectively across teams, drive designs from prototype to production, and communicate clearly with technical and non-technical partners.
• Track record of leading complex cross-team projects, setting technical direction, and making critical technical decisions that impact multiple teams or products.

Ways to stand out from the crowd:

• Experience building and operating data flywheels or large-scale data pipelines for ML, including data quality monitoring and continuous retraining loops.
• Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement/imitation learning for driving or robotics.
• Experience leveraging simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
• Contributions to sophisticated methods in data-centric ML, VLM/VLA, or autonomous driving, such as impactful publications, open-source projects, or widely used internal tools.
• Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications., Algorithms, Artificial Intelligence (AI), Autonomous Driving Systems, Cloning, Code Reviews, Communication Skills, Computer Engineering, Computer Science, Computer Skills, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Data Collection, Data Management, Data Quality, Data Sets, Debugging Skills, Deep Learning, GPU (Graphics Processing Unit), JAX (Java API for XML), Machine Learning, Open Source, Prototyping, Publications, Python Programming/Scripting Language, Quality Management, Quality Monitoring, Requirements Validation/Verification, Robotics, Simulation, Software Engineering, Team Player, Testing, Training Data Sets

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

NVIDIA is the world leader in graphics processing technologies, creating innovative, industry-changing products for computing, consumer electronics, and mobile devices. NVIDIA products are transforming visually-rich applications such as video games, film production, broadcasting, industrial design, space exploration, and medical imaging. We invest in our people and our technologies, support and fund industry research around the world, and consistently deliver high-quality products. NVIDIA’s culture promotes and inspires a team of world-class employees to be at the top of their game. We’ve created an environment where talents are recognized and collaboration is valued. Our employees are shaping the world of tomorrow. . . today. We invite you to explore the opportunities available at NVIDIA to see what your future may hold.

Company Size: 10,000 employees or more