Lead AI Research Scientist – Robotics

Job not on LinkedIn

🔥 4 minutes ago

🌐 United States, India – Remote

🇺🇸 United States – Remote 🇮🇳 India – Remote

⏳ Contract/Temporary

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Asiacruit

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤝 B2B

🎯 Recruiter

B2B • Recruitment

Asiacruit is an Employer of Record and Business Process Outsourcing (BPO) firm focused on helping companies hire employees, manage payroll, maintain compliance, and expand across Asia without the need to set up local legal entities. The company advertises job openings, provides regional HR and payroll services, and positions itself as a partner for cross-border hiring and workforce management; the site also highlights company culture recognition (Great Place to Work in the Philippines).

📋 Description

• 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

• 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

• 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