7 Mujoco Jobs

About Tonks AI Tonks AI accelerates simulation-to-real robotics by automating high-quality, physics-ready environment creation. Our platform empowers robotics teams to: Generate realistic training environments via text/image prompts Rapidly produce diverse, tailored scenarios Build on the NVIDIA Isaac Sim platform to set new benchmarks in simulation realism and scalability. Role Overview We seek aRobotics Simulation Engineerexperienced in Isaac Sim (or similar platforms), eager to design, build, and optimize advanced simulation environments for next-gen autonomous systems. Candidates will work closely with AI-driven scenario generation pipelines and support external customers by integrating ...

Company Description Renesas is one of the top global semiconductor companies in the world. We strive to develop a safer, healthier, greener, and smarter world, and our goal is to make every endpoint intelligent by offering product solutions in the automotive, industrial, infrastructure and IoT markets. Our robust product portfolio includes world leading MCUs, SoCs, Analog and power products, plus Winning Combination solutions that curate these complementary products. We are a key supplier to the world's leading manufacturers of electronics you rely on every day; you may not see our products, but they are all around you. Renesas employs roughly 21,000 people in more than 30 countries worldwid...

About CynLr As a foundational technology building company in Robotics & AI, CynLr builds visual robots that can intuitively learn to pick & handle even unknown objects without requiring any prior training , just like a human baby fiddling with objects. CynLr calls this stack Object Intelligence (OI). From fitting a screw to removing object out of its the plastic wrapper to automating the assembly of a car/gadget - every such object handling task that involves adapting on the fly is not prior trainable & thereby remains non-automatable across the industries. Wit h OI s ability to learn on the fly , CynLr's focus is to universally automate factories and eliminate the need for complicated custo...

We are looking for a Reinforcement Learning Engineer to design and deploy RL-based solutions for robotics, gaming, and complex decision-making systems.

About Tonks AI Tonks AI accelerates simulation-to-real robotics by automating high-quality, physics-ready environment creation. Our platform empowers robotics teams to: Generate realistic training environments via text/image prompts Rapidly produce diverse, tailored scenarios Build on the NVIDIA Isaac Sim platform to set new benchmarks in simulation realism and scalability. Role Overview We seek aRobotics Simulation Engineerexperienced in Isaac Sim (or similar platforms), eager to design, build, and optimize advanced simulation environments for next-gen autonomous systems. Candidates will work closely with AI-driven scenario generation pipelines and support external customers by integrating ...

Job Title: Simulation Expert (Sim/Middleware) Location: Vapi, Gujarat Employment Type: Full-Time Overview We are seeking an experienced **Simulation Expert (Sim/Middleware)** to own photorealistic and physics-accurate simulation, scenario generation, and CI-at-scale evaluations. This role will involve developing, maintaining, and optimizing simulation stacks for robotics testing, validation, and deployment readiness across multiple domains including humanoids, AGVs, cars, and drones. Key Responsibilities Deploy and manage simulation stacks such as Isaac Sim, Unity, Unreal Engine, Gazebo, and MuJoCo; support both HIL and SIL. Design and implement scenario generators, rare-event sampling, and ...

1.Design and implement simulation environments for robotic systems using platforms like Gazebo, Isaac Sim, Webots, Mujoco, or Unity. 2.Simulate sensor data (LiDAR, camera, IMU, etc.) and actuators with realistic physics and noise models. Required Candidate profile 3.Familiarity with modelling and simulating various sensors (LiDAR, depth camera, GPS, IMU, etc.) 4.Knowledge of autonomous navigation, SLAM, or robotic manipulation in simulated environments.