Research Scientist - Reinforcement Learning

Position Overview

In this role, you will drive the development of high-performing and resource-efficient reinforcement learning (RL) methods, tailored for the unique challenges of robotics, physical AI, and scheduling / OR systems. As a core member of the Digital Twins team, you will collaborate with researchers and ML engineers to design RL-driven solutions for complex industrial environments, and integrate them seamlessly with high-fidelity simulations and real-world data pipelines.

Responsibilities

• Design, implement, and optimize RL, imitation learning for a variety of systems including robotics, scheduling and routing.
• Build scalable, transferable, and production-ready codebases using PyTorch.
• Explore and prototype novel learning approaches that push the boundaries of efficiency and adaptability.
• Mentor and lead a team for publications, patents, and open research collaborations.

Ready to Apply?

Submit your application today and join our talented team at Quantiphi.

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