Senior Machine Learning Engineer - Generative Models

Job description

Job responsibilities

• Develop and advance diffusion and video generation models that power our Neural Simulation product, bringing the latest research into production to improve realism, controllability, and scalability
• Push the limits of generative simulation for driving scenes, including: Controllable generation conditioned on scene layout, camera pose, actors, and trajectories
• Temporally consistent, multi-camera video generation
• Augmenting real-world logs with new scenarios, actors, and conditions such as weather and lighting
• Combine generative models with our neural reconstruction pipeline to improve fidelity and coverage of simulated scenes
• Scale training and inference of large generative models for production workloads
• Define and build evaluation metrics, benchmarks, and validation workflows that measure realism, temporal consistency, controllability, and sim-to-real gap
• Work closely with customers to understand their pain points and implement technical solutions in the Neural Simulation product

Job requirements

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