Hybrid Machine Learning Research Scientist, Robotics VLAs Post-Training and Adaptation

at Tri-global Solutions Group Inc.

• Job title: Machine Learning Research Scientist, Robotics VLAs Post-Training and Adaptation
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $176,000 - $253,000 per year
• Degree requirement: Postgraduate Degree
• Tech skills: PyTorch
• Location requirements: Hybrid, Los Altos, United States

About the role

• Researcher at Toyota Research Institute advancing post-training methods for Vision-Language-Action models in robotics. Focusing on improving model alignment, robustness, and adaptability in real-world robotic settings.

Responsibilities

• Design and implement post-training pipelines for VLA models using techniques such as reinforcement learning (RL), reinforcement learning from human or preference feedback (RLHF/RLAIF), in-context learning.
• Develop methods to enhance real-world transferability of policies trained in simulation.
• Explore and implement reset-free and autonomous data collection strategies that enable continual skill improvement.
• Investigate exploration algorithms that balance safety, curiosity, and efficiency for data gathering.
• Lead the design of data collection and curation pipelines using multimodal data from demonstrations, teleoperation, and on-policy rollouts.
• Collaborate across teams in perception, control, and ML infrastructure to deploy scalable and reproducible research systems.
• Publish research outcomes and contribute to the open robotics and embodied AI communities.

Requirements

• Ph.D. or M.S. in Robotics, Machine Learning, Computer Vision, or related field, or equivalent applied research experience.
• Expertise in reinforcement learning, imitation learning, and multimodal representation learning.
• Strong proficiency with deep learning frameworks (e.g., PyTorch, JAX) and robotics simulation environments (e.g., MuJoCo, IsaacSim, PyBullet, Habitat).
• Experience with sim-to-real transfer, policy adaptation, or continual learning in embodied settings.
• Strong coding and experimental skills with an emphasis on reproducibility and evaluation at scale.
• Prior robotics experience with real-world hardware and ML-based robot deployments.

Benefits

• medical, dental, and vision insurance
• 401(k) eligibility
• paid time off benefits (including vacation, sick time, and parental leave)
• annual cash bonus structure