GPU-Driven Robotics Simulation Platform Engineer

Genesis AI; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Genesis AI in London is seeking a physics simulation engineer to help build core simulation infrastructure for robotics model development, evaluation and iteration. You will design scalable systems for running diverse simulation workloads across tasks, environments, and robots.

You’ll develop reusable environment frameworks and tooling that make simulation workflows more reliable and observable, bridge the sim-to-real gap with policy teams, and collaborate on a real-to-sim pipeline with the

Qualifications

• Experience in physics simulation engineering, with emphasis on robotics contexts.
• Ability to take ownership and drive problems to resolution.
• deep experience with rigid body simulation and FEM techniques.
• Provide insights from a robotic researcher/engineer’s perspective to improve UX.
• Proficiency in CUDA and GPU programming for high-performance computing.

Responsibilities

• Build core simulation-centered infrastructure for robotics model development, evaluation, and iteration.
• Design scalable systems for creating, running, and managing diverse simulation workloads across tasks, environments, and robots.
• Develop reusable environment frameworks, task interfaces, and tooling to improve reliability and observability.
• Bridge the sim-to-real gap with the policy training team.
• Develop a real-to-sim pipeline in collaboration with the asset generation team.
• Collaborate with a team building general-purpose Physical AI.

Skills

Physics simulation engineering

Ownership and initiative

Rigid body simulation

FEM

CUDA and GPU programming

Job description

Genesis AI in London is seeking a physics simulation engineer to help build core simulation infrastructure for robotics model development, evaluation and iteration. You will design scalable systems for running diverse simulation workloads across tasks, environments, and robots.

You’ll develop reusable environment frameworks and tooling that make simulation workflows more reliable and observable, bridge the sim-to-real gap with policy teams, and collaborate on a real-to-sim pipeline with the