Lead AI Research Scientist – Robotics

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Oversee the adaptation and creation of Vision-Language-Action models tailored for robotic applications.

• Fine-tune open-weight VLA models, including OpenVLA, Octo, and π0, for navigation and manipulation tasks.

• Create multimodal representations that link camera observations, natural-language instructions, spatial reasoning, and robotic actions.

• Develop strategies for action-tokenization and spatial waypoint generation to enhance robotic behavior.

• Establish parameter-efficient fine-tuning pipelines utilizing LoRA and other PEFT methodologies.

• Collaborate with vision-language models, Vision Transformers, and large multimodal frameworks.

• Integrate visual perception and AI functionalities into robotic decision-making systems.

• Investigate cross-embodiment learning and datasets like Open X-Embodiment.

• Partner with robotics controls and embedded systems teams to convert model outputs into actionable robot behaviors.

• Direct research planning, technical assessments, experimental procedures, and enhancements to model performance.

• Mentor researchers and engineers in model adaptation, training, evaluation, and deployment.

⛳️ Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Robotics, Machine Learning, or a related discipline.

• Minimum of 4 years of pertinent experience in multimodal AI, foundation models, vision-language models, imitation learning, or robotic learning.

• Significant experience in developing, training, or fine-tuning large multimodal models, Vision Transformers, or similar deep learning architectures.

• Strong command of Python and PyTorch or JAX.

• Practical experience with vision-language models or Vision-Language-Action (VLA) architectures.

• Familiarity with open-weight VLA models such as OpenVLA, Octo, or π0.

• Experience utilizing Hugging Face tools and engaging in model training or fine-tuning processes.

• Hands-on knowledge of parameter-efficient fine-tuning techniques, including LoRA or similar methods.

• Comprehension of multimodal representation learning, visual perception, and language-conditioned action generation.

• Familiarity with robotic imitation learning, policy learning, or reinforcement learning.

• Understanding of cross-embodiment robotic learning and datasets such as Open X-Embodiment is a plus.

• Capability to spearhead technical research, assess experimental outcomes, and translate research insights into practical AI functions.

🏝️ Benefits

• Opportunity to lead the advancement of innovative Physical AI and VLA technologies.

• Work at the cutting edge of multimodal AI, foundation models, and robotics.

• Explore novel methods for language-conditioned robotic navigation and manipulation.

• Collaborate with AI researchers and robotics engineers to translate findings into real-world applications.

• Influence the technical direction and research priorities for sophisticated AI systems.

• Enjoy a remote work arrangement with a US-based research team, subject to approved work locations.