AI Research Scientist

Title: Research Scientist, Intelligent Robotics Systems
Location: Vancouver, CA (Hybrid or On-Site)

About the Role:
A pioneering organization at the forefront of robotics and artificial intelligence is seeking a Research Scientist to drive advancements in autonomous robotic systems. This individual will help shape the future of intelligent robotics by leading research efforts in machine learning, decision-making under uncertainty, and adaptive system behavior. If you’re passionate about solving complex real-world challenges through AI-driven innovation, this is your opportunity to make a tangible impact.

This role offers a chance to publish groundbreaking research, contribute to real-world robotic deployments, and work alongside top-tier experts in a dynamic and resource-rich environment. You’ll help bridge the gap between theoretical innovation and applied robotics solutions in fast-moving, unstructured environments.

Key Responsibilities:

• Conduct original research in areas such as reinforcement learning, behavioral cloning, and uncertainty-aware planning for robotics applications.
• Build and refine algorithms that enable intelligent navigation, control, and interaction in dynamic physical settings.
• Lead experimentation efforts in both simulated and physical robotic platforms to validate research insights.
• Collaborate with cross-functional teams including software engineers, mechanical engineers, and AI specialists to integrate cutting-edge research into functional systems.
• Author and present high-impact research papers at top academic and industry conferences.
• Maintain fluency with emerging research literature and assess its potential for real-world deployment in intelligent systems.

Qualifications:

• Advanced degree (PhD preferred, MSc considered) in Computer Science, AI, Robotics, or related discipline.
• Track record of publishing in peer-reviewed venues such as ICRA, NeurIPS, CoRL, ICML, or RSS.
• Strong expertise in areas like reinforcement learning, imitation learning, probabilistic decision-making, or motion planning.
• Proficiency in Python and machine learning frameworks such as PyTorch, JAX, or TensorFlow.
• Hands-on experience with robotic simulation platforms (e.g., MuJoCo, Isaac Gym, or Gazebo) and reinforcement learning libraries (e.g., RLlib, Stable-Baselines3).
• Solid grounding in probability, optimization techniques, and system modeling.

Preferred Skills:

• Experience applying AI techniques to real-world robotic systems and physical hardware.
• Familiarity with robotic middleware tools such as ROS, as well as experience working with real-time systems.
• Knowledge of hierarchical control structures, model-based learning approaches, or multi-agent systems.
• Contributions to open-source initiatives or academic collaborations in the robotics or machine learning space.

What’s in It for You:

• Opportunity to contribute to field-defining research with real-world deployment.
• Competitive compensation package including research stipends and performance incentives.
• Collaborative, innovation-first culture with flexible hybrid work options.
• Access to advanced robotics infrastructure and a team of like-minded technologists.

Apply today to help drive the next generation of intelligent machines.