Senior Research Engineer

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

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 autonomous 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/JAX.
. 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.
. Independently identify opportunities, propose solutions, and execute with minimal oversight while aligning with evolving company needs. Must-Have Qualifications
. Ph.D. or M.S. in Computer Science, Artificial Intelligence, Robotics, Engineering, Operations Research or a closely related field, with strong emphasis on RL.
. (PhD + 2) / (MTech + 5) years of research experience in RL with a strong publication record in top venues
. Strong programming skills in Python, with proven expertise in PyTorch or JAX, and a track record of writing clean, modular, and deployable code.
. Solid foundation in machine learning with specialization in RL, imitation learning.
. Familiarity with advanced ML architectures such as graphs and transformers.
. Self-starter mindset: industrious, independent, and able to generate ideas and drive them forward without waiting for direction.
. Excellent problem-solving skills and adaptability to shifting research directions.
. Strong collaboration skills, with experience working in interdisciplinary and fast-paced teams. Nice-to-Have Qualifications
. Familiarity with LLMs, agentic AI and vision models is a plus.