Senior Machine Learning Engineer - Generative Models

The role

You will develop and advance diffusion and video generation models for the Neural Simulation product. This involves creating realistic, controllable sensor data and augmenting real-world logs with new scenarios.

What you will do

• Develop and advance diffusion and video generation models
• Push the limits of generative simulation for driving scenes
• Create controllable generation conditioned on scene layout, camera pose, actors, and trajectories
• Generate temporally consistent, multi-camera video
• Augment real-world logs with new scenarios, actors, and conditions
• Combine generative models with neural reconstruction pipelines
• Scale training and inference of large generative models for production workloads
• Define and build evaluation metrics, benchmarks, and validation workflows
• Work closely with customers to implement technical solutions
• Collaborate with Infra, Autonomy, Research and other product teams

Required qualifications

• 5+ years of experience developing and shipping ML or computer vision systems
• Minimum of a Bachelor's degree in computer science, physics, robotics, or equivalent
• Strong hands-on experience with diffusion models and video generation
• Solid foundation in generative modeling and deep learning, including training and fine-tuning large models
• Proficiency in Python and PyTorch
• Ability to turn research ideas into robust, production-quality software
• Strong problem-solving skills and comfort with ambiguity

Nice to have

• Experience with learning-based 3D reconstruction, such as 3D Gaussian Splatting, NeRFs, or feed-forward Gaussian Splatting
• Background in computer vision (e.g., SfM, SLAM, photogrammetry) and/or computer graphics (e.g., rendering, rasterization, ray tracing)
• Track record of shipping ML products with clearly defined evaluation metrics and benchmarks
• Experience in autonomous driving or robotics, including working with multi-sensor data (camera, LiDAR, radar)
• Experience with 3D-aware or multi-view consistent generation, or world models
• Experience with large-scale distributed training and inference optimization (e.g., distillation, efficient sampling)
• Programming experience in C++ and/or CUDA
• Peer-reviewed research at conferences such as CVPR, ICCV/ECCV, NeurIPS, ICLR, ICML, or SIGGRAPH
• A Master's degree or PhD in computer science, physics, robotics, or related fields

About the company

Applied Intuition, Inc. is a Silicon Valley company creating digital infrastructure for physical AI. It services the automotive, defense, trucking, construction, mining and agriculture industries.