Senior Machine Learning Engineer – Predictive World Model
Tasks
- Apply predictive pre training for Vision Language Action driving
- Build shared backbone for prediction and trajectories
- Define evaluation methodology for world models
- Develop multi view future prediction and generation
- Evaluate representation quality prediction accuracy generation fidelity physical plausibility long horizon rollouts
- Extend prediction into multimodal latent space
- Feed synthetic data and corner case simulations into training
- Forecast future scene states
- Implement 3D scene representations using Gaussian Splatting
- Implement action conditioned rollouts
- Implement action free future forecasting
- Research and develop predictive world models
Perks/Benefits
- Computational resources
- Dinners
- Fun activities
- In house infrastructure
- Lunches
- Snacks
- Supportive work environment
Skills/Tech-stack
Computer Vision | Data Processing | Deep learning | DeepSpeed | Diffusion Models | Distributed Training | FSDP | Flow matching | Gaussian Splatting | Generative Modeling | Kernel optimization | Large Scale Data | Large-scale | Large-scale Data Processing | Machine Learning | Megatron | Mixed Precision | Model-based reinforcement learning | Multimodal Learning | Nerf | Neural Rendering | Neural Scene Representations | PyTorch | Python | Reinforcement Learning | Scene representations | Torch compile | Transformer | Variational Autoencoder | Video Tokenizers | Vision-language | Vision-language-action
Education
Regions
Countries
States
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