Lead AI Research Scientist Robotics

AsiaCruit, Inc.; New Delhi; A distancia; INR 3.500.000 - 6.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Hybrid in New Delhi

Descripción de la vacante

Asiacruit is seeking a Lead Physical AI / Vision-Language-Action Research Scientist to lead development and adaptation of foundation models that connect visual perception, language understanding, and robotic actions. This role guides research and implementation for robots to interpret visuals, follow natural-language instructions, and generate executable actions for navigation and manipulation.

The position blends multimodal AI, open-weight VLA models such as OpenVLA/OpenX-Embodiment, and PEFT

Formación

• Masters or PhD in Computer Science, AI, Robotics or ML.
• 4+ years in multimodal AI, foundation models, VLMs or robotic learning.
• Experience with large multimodal models, ViT, and deep learning architectures.
• Proficiency in Python and PyTorch or JAX.
• Hands-on with VLA architectures and open-weight VLA models like OpenVLA/Octo/pi0.
• Familiarity with Hugging Face tools and fine-tuning workflows.
• Knowledge of PEFT techniques (LoRA) and multimodal representation learning.
• Understanding of robotic imitation learning, policy learning or RL.

Responsabilidades

• Lead adaptation and development of Vision-Language-Action models for robotic apps.
• Fine-tune open-weight VLA models for navigation and manipulation.
• Develop multimodal representations linking camera, language, and robot actions.
• Design action-tokenization and spatial waypoint generation for robotic behavior.
• Develop PEFT pipelines (LoRA and related methods).
• Work with ViT and large multimodal models; integrate perception into decision-making.
• Explore cross-embodiment learning and datasets like Open X-Embodiment.
• Collaborate with robotics controls and embedded teams to deploy behaviors.
• Lead research planning, evaluation, experiments and performance improvements.
• Guide researchers in model adaptation, training, evaluation, and deployment.

Conocimientos

Python

PyTorch or JAX

Multimodal AI

Vision-Language Models

Educación

Masters or PhD in Computer Science/AI/Robotics/ML

Herramientas

OpenVLA family

Hugging Face tools

LoRA/PEFT tools

Vision Transformers (ViT)

Descripción del empleo

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 behaviors.

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

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

Qualifications

• Masters 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 employers approved work locations.