Lead AI Research Scientist (Robotics)

Asiacruit BPO, Inc.; New Delhi; Hybrid; INR 4,000,000 - 6,000,000; Full time

Job summary

Asiacruit BPO, Inc. in Delhi seeks a Lead Physical AI / Vision-Language-Action (VLA) Research Scientist to steer foundation-model adaptation for robotic perception and action.

You’ll guide multimodal research, model fine-tuning, and integration into real-world robotic systems. The role combines cutting-edge vision-language models with robotics, requiring strong Python/PyTorch/JAX expertise and a track record of leading research efforts from idea to deployment.

Qualifications

• 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.

Responsibilities

• 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 that connect 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 techniques such as LoRA and other PEFT methods.
• Work with vision-language models, Vision Transformers (ViT), 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 to improve model generalization across robotic platforms.
• Collaborate with robotics controls and embedded systems teams to translate model outputs into executable robot behaviours.
• Lead research planning, technical evaluations, experiments, and model performance improvements.
• Guide researchers and engineers in model adaptation, training, evaluation, and deployment.

Skills

Python

PyTorch

JAX

Vision Transformers

PEFT LoRA

OpenVLA

OpenX-Embodiment

Hugging Face

Robotics

Education

Master's or Ph.D. in CS/AI/Robotics

Tools

Hugging Face tools

Vision-Language-Action frameworks

Job description

About Asiacruit

At Asiacruit, we connect top talent with forward-thinking organizations across industries. Our mission is to help businesses grow through smart, strategic, and people-focused solutions. We support companies by providing high-quality talent for local and global markets.

Position Overview

We are looking for a Lead Physical AI / Vision-Language-Action (VLA) Research Scientist to lead the development and adaptation of foundation models that connect visual perception, language understanding, and robotic actions.

You will guide research and implementation efforts to help robots interpret visual information, understand natural-language instructions, and generate meaningful actions for navigation and manipulation. The role combines multimodal AI, foundation model adaptation, robotic learning, and applied computer vision.

Key Responsibilities

• 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 that connect 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 techniques such as LoRA and other PEFT methods.

• Work with vision-language models, Vision Transformers (ViT), 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 to improve model generalization across robotic platforms.

• Collaborate with robotics controls and embedded systems teams to translate model outputs into executable robot behaviours.

• Lead research planning, technical evaluations, experiments, and model performance improvements.

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

Qualifications

• 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.

Why Join?

• 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.

Work Location & Arrangement

Remote through a US-based research team, or hybrid in New Delhi, India. Remote eligibility is subject to the employer's approved work locations.