Robotic AI Engineer​/Applied Scientist - Foundation Models

Robotic AI Engineer/Applied Scientist - Foundation Models

We are seeking an exceptional AI Foundation Model Engineer to design, implement, test, and deploy state‑of‑the‑art foundation models on our robots.

• Develop, fine‑tune, and optimize foundation models for the robot, leveraging advanced techniques such as pretraining, fine‑tuning, and retrieval‑augmented generation (RAG).
• Translate high‑level application goals into foundational AI solutions, delivering robust and scalable models that perform effectively in real‑world scenarios.
• Build pipelines for training, evaluation, and deployment of models on various platforms, ensuring high performance and adaptability across diverse use cases.
• Stay at the forefront of research, incorporating cutting‑edge advancements in AI and foundation models to enhance system capabilities and push technical boundaries.
• Own critical projects end‑to‑end, from model design and experimentation to deployment and continuous improvement.
• Collaborate with cross‑functional teams, including data, software, and systems engineers, to integrate models seamlessly into production workflows.

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Deep understanding of machine learning concepts, including attention mechanisms, transformers, and training techniques.
• Experience working with fine‑tuning, retrieval‑augmented generation (RAG), prompt engineering, or reinforcement learning with human feedback (RLHF).
• Proficiency in programming languages and tools commonly used in machine learning (e.g. Python).
• A strong grasp of theoretical concepts and practical implementation of multimodal foundation models.

• Experience with deployment of models to edge devices for real‑time inference.
• Experience with large‑scale distributed training and optimization frameworks (e.g. PyTorch, Tensor Flow) and familiarity with tools for model compression and quantization.
• General knowledge of robotics principles, including kinematics, dynamics, and control.
• Publications or contributions to the machine learning community, particularly in areas related to robotics or large language models.
• Excellent problem‑solving skills, with the ability to innovate and experiment with novel approaches.