AI Robotics Engineer — Simulation, RL & Diffusion Policies

We are looking for a highly skilled AI Robotics Developer to build scalable simulation pipelines and train state-of-the-art robotic policies. If you excel at turning physics simulations into rich training grounds and leveraging that data for advanced RL and Imitation Learning, we want you on our team. What You'll Be Doing Simulation & Environment Design: Build and maintain highly diverse, physics-accurate simulation environments using MuJoCo or NVIDIA Isaac Sim to ensure robust policy generalization. Synthetic Data Generation: Architect pipelines to generate large-scale, high-quality synthetic "human-like" demonstration data entirely within simulation. Reinforcement Learning: Utilize generated simulation data to train robust control policies using PPO, GRPO, or similar algorithms. Imitation Learning & Continuous Control: Train models to output continuous action values using cutting-edge approaches like Diffusion Policies or Flow Matching. Standard Imitation Learning (Behavior Cloning) experience is also highly valued. Fine-Tuning & Alignment: Apply Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) to refine robotic behaviors and improve policy reliability. What We’re Looking For Deep Simulation Expertise: Hands-on experience with MuJoCo, Isaac Sim, or similar physics engines. You know how to randomize domains and build environments that prevent policies from overfitting. Policy Training Experience: Strong background in applying RL (PPO/GRPO) or Imitation Learning to robotic control tasks. Modern Architecture Knowledge: Familiarity with continuous-value generation models (Diffusion models, Flow Matching) applied to robotics. PyTorch & GPU Proficiency: Comfort building complex training loops and scaling them across GPU clusters. Nice to Have Experience bridging the "Sim-to-Real" gap and deploying policies trained in simulation onto physical hardware. Contributions to open-source RL or robotics simulation frameworks. Screening Question (Required) Please answer the following question in your application. Proposals without this answer will not be considered: "What are the top 3 most difficult technical problems you have solved related to simulation or policy training? Describe each in 5 sentences (15 total)." Engagement Details Type: Contract (with potential for long-term engagement) Availability: Immediate start preferred Hours: Full-time (Fixed price) If you are passionate about pushing the boundaries of embodied AI through simulation and advanced training methodologies, apply below! Strong candidates will be shortlisted for a personal interview.