Senior Machine Learning Engineer - Physical AI and Synthetic Data Generation

Details

We are looking for outstanding Machine Learning Engineers to join our Physical AI teams. This role is at the forefront of Physical AI, developing sophisticated generative pipelines to build high-fidelity synthetic datasets. It leverages state-of-the-art multimodal models and diffusion techniques to simulate complex physical environments, ensuring AI agents are trained on diverse and rigorous data. The work supports users of synthetic datasets, including policy models, and contributes to technology for future autonomous systems.

Responsibilities

• Architect generative pipelines: develop and implement advanced image and video generation, editing, and reasoning models to produce high-fidelity synthetic data for Physical AI applications.
• Multimodal development: build and fine-tune large-scale models, including VLMs and MLLMs, applying transformer, auto-regressive and diffusion-based architectures.
• Controllable synthesis: apply and evolve user controls during data generation to ensure precise environmental and structural control over generated data.
• Detailed validation: establish KPI evaluation and validation processes to ensure quality and physical accuracy of synthetic releases.
• Automated quality assurance: build and test automated data QA pipelines using a mix of classical computer vision algorithms and VLMs.
• SOTA data engineering: lead generation of massive training datasets using state-of-the-art tools and synthetic data mining techniques.
• Contribute to full ML software lifecycle including performance optimization, testing, and high-quality documentation.

Requirements

• BS, MS, or PhD in Computer Science, Computer Graphics, Robotics, or a related field (or equivalent experience).
• 12+ years of experience in ML software development.
• Deep technical knowledge of image/video synthesis, including diffusion models and state-of-the-art multimodal methods.
• Strong hands-on skills in major DNN libraries and programming languages, including Python.
• Experience with workflow management and databases to facilitate large-scale training and data generation.
• Strong analytical and mathematical skills to bridge data-driven approaches and physical-world constraints.
• Experience assessing the impact of synthetic data on model performance through metrics and systematic validation.
• Collaborative communication skills and ability to work in a tightly-knit team.

Ways to Stand Out

• Experience with computer/GPU architecture to improve performance during inference/training.
• Familiarity with simulation platforms and deep understanding of 3D sensor modalities (camera, multi-camera setups, LiDAR, radar).
• Experience with open source software.

Compensation & Benefits

• Base salary ranges (determined by location, experience, and internal pay):
  • Level 5: 224,000 USD - 356,500 USD
  • Level 6: 272,000 USD - 431,250 USD
• Eligible for equity and benefits.

Additional Information

• Applications accepted at least until May 15, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.