Lead AI Research Scientist (Robotics)
New
J
JobgetherAI robotics
Based in the United StatesFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- At least 4 years of relevant professional experience
- Required Skills
- PythonPyTorchComputer Vision
Requirements
- Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, Machine Learning, or a related technical discipline.
- At least 4 years of relevant professional experience in multimodal AI, foundation models, vision-language models, imitation learning, or robotic learning.
- Hands-on experience developing, training, and fine-tuning large multimodal models, Vision Transformers, or related deep learning architectures.
- Advanced proficiency in Python and deep learning frameworks such as PyTorch or JAX.
- Practical experience with Vision-Language Models or Vision-Language-Action architectures.
- Familiarity with open-weight VLA models such as OpenVLA, Octo, and π0.
- Experience with Hugging Face tools and model training, adaptation, and fine-tuning workflows.
- Knowledge of parameter-efficient fine-tuning techniques, including LoRA and related approaches.
- Strong knowledge of multimodal representation learning, computer vision, visual perception, and language-conditioned action generation.
- Familiarity with robotic imitation learning, policy learning, and/or reinforcement learning.
- Ability to lead technical research initiatives, assess experimental outcomes, and translate findings into practical AI capabilities.
- Ability to provide technical direction, mentor colleagues, and drive research projects from experimentation to implementation.
Responsibilities
- Lead research, development, and adaptation of Vision-Language-Action models for robotic applications.
- Fine-tune open-weight VLA models, including OpenVLA, Octo, and π0, for navigation and manipulation tasks.
- Develop multimodal representations linking camera observations, natural-language instructions, spatial reasoning, and robotic actions.
- Design action-tokenization strategies and spatial waypoint generation methods.
- Build and optimize parameter-efficient fine-tuning pipelines using LoRA and other PEFT techniques.
- Integrate AI-driven visual perception and reasoning into robotic decision-making systems.
- Explore cross-embodiment learning approaches and datasets such as Open X-Embodiment.
- Collaborate with robotics control and embedded systems teams to translate model outputs into executable robotic behaviors.
- Lead research planning, technical evaluations, experimentation, and model performance improvements.
- Mentor researchers and engineers through model adaptation, training, evaluation, and deployment.
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