Senior Robotics Research Engineer, Robotics and AI for Drug Discovery

NVIDIA•Santa Clara, CA

9d•$184,000 - $356,500

About The Position

NVIDIA is seeking a Senior Robotics Research Engineer to develop fundamental robotics technology and real-world automation and autonomy systems for molecular discovery, manufacturing, testing, and validation. The role is part of the Seattle Robotics Lab’s work with the NVIDIA + Eli Lilly Co-innovation AI Lab, building physical AI for wet laboratories with scientists in the loop. The engineer will work across the robotics stack, including simulation, perception, planning, learning, control, and real-world systems integration. The role involves translating research into mature automation and autonomy capabilities for biological experiment workflows, collaborating with robotics researchers and specialists in computational biology, chemistry, generative and agentic AI, bioinformatics, and simulation. The position may also involve co-authoring publications in high-impact journals and conferences.

Requirements

PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field, or equivalent experience.
At least 3 years of research and engineering experience after completing a PhD.
Deep knowledge of robotics and AI theory and practice, particularly real-world robotics applications.
Exceptional communication, collaboration, and interpersonal skills, with substantial experience contributing to teams as both a leader and an individual contributor.
Exceptional programming skills in Python.
Track record of writing clean, high-quality code collaboratively using standard software engineering practices such as unit testing, version control, and CI/CD.
Fluency in modern deep learning frameworks such as PyTorch and JAX, and experience training deep learning models on GPU clusters.
Significant experience with robotics frameworks such as ROS2 and physics simulation frameworks such as Isaac Sim, Isaac Lab, and MuJoCo.
Ability to work through complexities in simulation and real-world robotics, including debugging physics simulators and renderers, selecting and maintaining robotics hardware, debugging communication systems, and designing robust model training and evaluation workflows.
Willingness to experiment with rapidly developing robotics and AI technologies and quickly learn biology and chemistry fundamentals, laboratory tasks and hardware, laboratory automation standards, and safety and regulatory constraints.

Nice To Haves

5 or more years of research and engineering experience after completing a PhD.
Familiarity with C++, CUDA, and Warp.
Direct experience in scientific and laboratory automation.
Expertise in bimanual manipulation.
Expertise in mobile manipulation and humanoid loco-manipulation.
Expertise in simulation, sim-to-real, and real-to-sim.
Expertise in multisensory perception, including vision, force/torque, and tactile sensing.
Expertise in task and motion planning.
Expertise in grasp and manipulation planning.
Expertise in imitation learning and reinforcement learning.
Expertise in high-performance control.
Expertise in robotics foundation models.

Responsibilities

Build digital twins of robots, laboratory environments, and scientific procedures using NVIDIA Isaac Sim, Isaac Lab, and Matterix.
Simulate robot and environment physics using NVIDIA Newton, including articulated rigid bodies, deformable objects, granular media, and fluids.
Develop perception pipelines for object detection, pose estimation, and tracking using multisensory inputs and foundation models.
Translate experimental protocols into executable physical procedures and smooth, collision-free trajectories using vision-language models and task and motion planning pipelines.
Train robots for contact-rich manipulation tasks using imitation learning, reinforcement learning, and high-performance control.
Build reliable and efficient real-world systems for discovery, manufacturing, testing, and validation procedures.
Integrate robotics systems into real-world biological experiment workflows.
Collaborate with Seattle Robotics Lab scientists to advance early-stage research and integrate it into a mature automation and autonomy stack.
Collaborate with research scientists and engineers in the NVIDIA + Lilly Co-innovation AI Lab across fields including computational biology and chemistry, generative and agentic AI, bioinformatics, and simulation.
Periodically co-author publications on technological achievements in high-impact scientific journals and conferences.