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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in developing and fine-tuning Vision-Language-Action models for robotic applications, with a strong foundation in multimodal AI and deep learning architectures. Proficient in integrating visual perception and AI capabilities into robotic decision-making systems while leading research and guiding teams in model adaptation and deployment.
Highest-signal resume keywords
Vision-Language-Action Model DevelopmentMultimodal AI ExpertisePython ProficiencyFine-Tuning Techniques (LoRA)Vision Transformers Experience
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Lead the adaptation and development of Vision-Language-Action models for robotic applications
- Fine-tune open-weight VLA models such as OpenVLA, Octo, and π0 for navigation and manipulation tasks
- Develop multimodal representations connecting camera observations, natural-language instructions, spatial reasoning, and robot actions
- Design action-tokenization and spatial waypoint generation approaches for robotic behavior
- Develop parameter-efficient fine-tuning pipelines using LoRA and other PEFT methods
- Work with vision-language models, Vision Transformers, and large multimodal models
- Integrate visual perception and AI capabilities into robotic decision-making systems
- Explore cross-embodiment learning and datasets such as Open X-Embodiment
- Collaborate with robotics controls and embedded systems teams to translate model outputs into executable robot behaviors
- Lead research planning, technical evaluations, experiments, and model performance improvements
- Guide researchers and engineers in model adaptation, training, evaluation, and deployment
Requirements
What you’ll need- Master's or Ph.D. in Computer Science, Artificial Intelligence, Robotics, Machine Learning, or a related field
- At least 4 years of relevant experience in multimodal AI, foundation models, vision-language models, imitation learning, or robotic learning
- Strong experience developing, training, or fine-tuning large multimodal models, Vision Transformers, or related deep learning architectures
- Strong proficiency in Python and PyTorch or JAX
- Hands-on experience with vision-language models or Vision-Language-Action (VLA) architectures
- Familiarity with open-weight VLA models such as OpenVLA, Octo, or π0
- Experience with Hugging Face tools and model training or fine-tuning workflows
- Practical knowledge of parameter-efficient fine-tuning techniques, including LoRA or related methods
- Understanding 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 an advantage
- Ability to lead technical research, evaluate experimental results, and translate research findings into practical AI capabilities
Benefits
Comp & perks- Opportunity to lead the development of emerging Physical AI and VLA technologies
- Work at the intersection of multimodal AI, foundation models, and robotics
- Explore new approaches to language-conditioned robotic navigation and manipulation
- Collaborate with AI researchers and robotics engineers to translate research into real-world applications
- Shape technical direction and research priorities for advanced AI systems
- Remote work arrangement through a US-based research team, subject to approved work locations
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Vision-Language-Action ModelsMultimodal Representation LearningDeep Learning ArchitecturesRobotic Imitation LearningParameter-Efficient Fine-TuningModel Training and EvaluationSpatial ReasoningAction-TokenizationNavigation and Manipulation TasksCross-Embodiment Learning
Soft Skills
LeadershipCollaborationResearch PlanningTechnical EvaluationGuidance and Mentoring
Tools & Technologies
PyTorchJAXHugging FaceOpenVLAOctoΠ0Vision TransformersAI Capabilities IntegrationRobotics ControlsEmbedded Systems
Certifications & Qualifications
Master's or Ph.D. in Computer ScienceArtificial IntelligenceRoboticsMachine Learning
Industry Keywords
Multimodal AIFoundation ModelsImitation LearningReinforcement LearningVisual PerceptionLanguage-Conditioned Action GenerationOpen X-Embodiment Datasets