Embodied AI / Simulation Engineer

Who we are: Formic is on a mission to reshape American manufacturing by making automation accessible to every factory. As labor constraints rise, costs increase, and global competition intensifies, automation is no longer optional for manufacturers that want to stay competitive. We deliver automation through a Robotics-as-a-Service model that combines industrial robotics, proprietary software, and full-service support into a single, integrated solution. By removing the traditional barriers of cost, complexity, and risk, we enable manufacturers to deploy automation quickly and realize measurable gains in throughput, safety, and operational efficiency without large upfront capital investment. Backed by leading investors including Lux Capital, Initialized Capital, Blackhorn Ventures, and Mitsubishi HC Capital North America, Formic is scaling rapidly and building the foundation for a new era of high-performance, Made in America production. About the team: The Software Engineering Team builds and operates the systems that power Formic’s Robotics-as-a-Service platform. Engineering focuses on ensuring deployed systems are observable, resilient, and remotely diagnosable at scale. The team builds production-grade edge and cloud systems that support reliable data collection, remote troubleshooting, live video streaming, and continuous system improvement. This work directly impacts fleet uptime, service efficiency, and customer outcomes by ensuring Formic’s monitoring and control infrastructure remains scalable, reliable, and continuously evolving. In this role you will: Design and train learning-based manipulation systems for humanoid and mobile manipulation platforms Develop and maintain high-fidelity digital twins using Isaac Sim, MuJoCo, or similar tools Implement and evaluate approaches such as: Action Chunking with Transformers (ACT) Diffusion Policies Behavior Cloning at Scale Vision-Language-Action (VLA) models Latent action or hierarchical skill models Work with modern foundation models for robotics (e.g., Pi0, Gemini ER 1.6 or similar), including adapting, fine-tuning, and deploying them for real-world tasks Contribute to development of a Universal Manipulation Interface (UMI) abstraction layer Build teleoperation-to-training data pipelines Design sim-to-real transfer strategies including domain randomization and system identification Evaluate policy robustness, generalization, and real-world performance Work closely with perception and controls teams to ensure stable closed-loop visuomotor policies Deploy, tune, and iterate on models running on real robotic systems in production environments What makes you a great fit: *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-69a66421-5e48-8328-aaba-65602d679977-47" data-testid="conversation-turn-30" data-scroll-anchor="true" data-turn="assistant"> Experience training embodied AI policies for real robots Familiarity with transformer-based action models (e.g., ACT) Experience with diffusion policies or other generative control methods Experience working with or adapting large-scale models (e.g., Pi0, Gemini ER 1.6, or similar VLA / multimodal models) Ability to deploy, fine-tune, and optimize models for real-world robotic systems (latency, robustness, reliability) Strong understanding of sim-to-real challenges Experience working with multi-modal inputs (vision, proprioception, language) Proficiency in Python and deep learning frameworks (PyTorch, JAX, etc.) Experience integrating learned policies with real-time control systems Strong experimental design, evaluation, and debugging skills Our Total Rewards: At Formic, we believe people do their best work when they feel supported both professionally and personally. That’s why we offer a comprehensive benefits and perks package for full-time, U.S.-based team members, including: Equity in Formic: Participate in our stock option program and share in the success of a fast-growing s