Senior Machine Learning Engineer, End-to-End Autonomous Driving

Details

We are seeking a Senior Machine Learning Engineer to join the end-to-end autonomous driving team. You will help build, train, and deploy large-scale end-to-end driving models that leverage VLM/VLA architectures and build a data flywheel that continuously improves systems in the real world.

NVIDIA is using AI to define the next era of computing, with GPUs powering computers, robots, and self-driving cars that can understand the world. The company offers a diverse and supportive environment focused on innovation and collaboration.

Responsibilities

• Design, implement, and train large-scale end-to-end driving models.
• Drive the data flywheel by identifying failure cases, specifying data collection and labeling needs, and iterating models to close real-world performance gaps.
• Build, curate, and maintain high-quality multimodal datasets, including video, sensor, and language/action traces, tailored for end-to-end autonomous driving.
• Develop and apply data-centric learning algorithms, including active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi-supervised or self-supervised methods.
• Explore and productize new data sources, including simulation, synthetic data, and world-model-based generation and augmentation, to improve coverage and robustness.
• Design and implement agentic data workflows that automate data discovery, labeling, evaluation, and retraining to maximize development velocity.
• Foster collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.

Requirements

• PhD with 4 or more years of experience, MS with 6 or more years of experience, or BS or equivalent experience with 8 or more 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, including data preprocessing, distributed training, evaluation, debugging, and iterative improvement.
• Practical experience with data-centric methods such as active learning, curriculum learning, outlier or novelty detection, or large-scale sample mining.
• Proficiency in Python and at least one major deep learning framework: PyTorch, TensorFlow, or JAX.
• Solid software engineering practices, including testing, code review, and CI/CD.
• 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 affecting multiple teams or products.

Preferred Qualifications

• Experience building and operating ML data flywheels or large-scale data pipelines, including data quality monitoring and continuous retraining loops.
• Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement or imitation learning for driving or robotics.
• Experience using simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
• Contributions to data-centric ML, VLM/VLA, or autonomous driving through 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.

Compensation and Benefits

The base salary range is $184,000–$287,500 USD for Level 4 and $224,000–$356,500 USD for Level 5. Salary is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until June 13, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.