About this role
Accountabilities:: Lead the research, development, and adaptation of Vision-Language-Action (VLA) models for advanced robotic applications. Fine-tune open-weight VLA models, including OpenVLA, Octo, and π0, for robotic navigation and manipulation tasks. Develop multimodal representations connecting camera observations, natural-language instructions, spatial reasoning, and robotic actions. Design action-tokenization strategies and spatial waypoint generation methods to improve robotic behavior and decision-making. Build and optimize parameter-efficient fine-tuning pipelines using LoRA and other PEFT techniques. Leverage Vision-Language Models (VLMs), Vision Transformers (ViT), and large multimodal models to enhance robotic perception and intelligence. Integrate AI-driven visual perception and reasoning capabilities into robotic decision-making systems. Explore cross-embodiment learning approaches and datasets such as Open X-Embodiment to improve generalization across different robotic platforms. Collaborate with robotics control and embedded systems teams to translate AI model outputs into executable robotic behaviors. Lead research planning, technical evaluations, experimentation, and continuous model performance improvements. Mentor and guide researchers and engineers throughout model adaptation, training, evaluation, and deployment processes. Translate research findings into practical, scalable AI solutions for real-world robotic applications. 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. Strong 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 working with Vision-Language Models (VLMs) or Vision-Language-Action (VLA) architectures. Familiarity with open-weight VLA models such as OpenVLA, Octo, and π0. Experience using Hugging Face tools and model training, adaptation, and fine-tuning workflows. Solid understanding 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. Understanding of cross-embodiment robotic learning and datasets such as Open X-Embodiment is considered an advantage. Demonstrated ability to lead technical research initiatives, assess experimental outcomes, and translate findings into practical AI capabilities. Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively across multidisciplinary research and engineering teams. Proven ability to provide technical direction, mentor colleagues, and drive research projects from experimentation to implementation. Benefits: Fully remote working arrangement through a US-based research team, subject to approved employer work locations. Opportunity to lead the development of emerging Physical AI and Vision-Language-Action technologies. Exposure to cutting-edge research at the intersection of multimodal AI, foundation models, and robotics. Opportunity to explore innovative approaches to language-conditioned robotic navigation and manipulation. Collaboration with AI researchers and robotics engineers on advanced, real-world applications. Significant influence over technical direction, research priorities, and the evolution of intelligent robotic systems. Contract-based employment arrangement. Alternative hybrid working arrangement may be available in New Delhi, India, subject to employer approval. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1
- LOCATION
- Remote · US, United States
- WORK MODE
- Remote
- JOB TYPE
- Full-time
- POSTED
- Nov 2, 2026
Source: Jobgether Careers