Member of Technical Staff, Research Engineer
Research Engineer develops and experiments with multimodal world models, focusing on data strategies, training techniques, evaluations, and production deployment for AI simulation technologies. Requires 4+ years in ML research/engineering and proficiency in PyTorch or JAX.
About the job
Responsibilities
- Run experiments to teach world models new behaviors — action following, scene manipulation, camera control, and beyond
- Develop and test new data strategies, architectural variants, and training techniques
- Design evaluations that measure model capabilities, and use them to drive model improvement
- Take features from research prototype to production, collaborating with product and creative teams to address application-specific gaps
- Contribute across the entire stack (data pipelines, modeling, production inference) to move projects forward
Requirements
- 4+ years of experience in machine learning research or engineering
- Familiarity with the architecture, training, and inference of large-scale multimodal generative models
- Experience building robust data pipelines for pretraining and post-training
- Comfort working across the full research stack: data, training, evaluation, and deployment
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and experience with distributed training at scale
- Ability to context-switch quickly and drive projects forward in a fast-moving, ambiguous environment
- Excitement about building AI that simulates the world
Skills
PyTorch, JAX, Multimodal Generative Models, Distributed Training, Data Pipelines, Machine Learning, Rl, Sft, World Models
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