The Role
Design and implement robust bimanual manipulation algorithms and train learning-based robot policies (diffusion, imitation, RL). Build end-to-end autonomy connecting perception, semantic task understanding, and low-level control. Ship production-quality Python and C++ code, profile and scale the autonomy stack, and work with high-fidelity simulators for sim-to-real transfer.
Summary Generated by Built In
Company Description
Role Description
What You’ll Do
Qualifications
Why Join Us
Autonomique is at the forefront of innovation in Physical AI, addressing key challenges in autonomy such as perception, reasoning, and dexterity. Our robotics intelligence framework delivers reliable, autonomous solutions for industries with complex operational demands. With advanced bi-manual robots, we are enabling groundbreaking advancements in manufacturing by empowering robots to perform critical real-world tasks. We are driven by the mission to make autonomous systems practical and impactful today.
This is a high-impact, high-ownership role for a builder who wants to shape our technical roadmap alongside the leadership team. You will work directly with the founding team to architect the core systems that define our robot's capabilities. We are looking for someone who values significant equity participation and wants to capture the upside of the value they create. You won't just be an employee; you will be a key architect of our success.
- Deploy Robust Manipulation Algorithms: Design and implement algorithms for complex bimanual tasks — pick/place, insertion, tool use — that perform reliably in dynamic industrial environments, not just in the lab.
- Develop Learning-Based Behaviors: Train robot policies using Diffusion Policy, imitation learning, and reinforcement learning to improve performance, robustness, and failure recovery.
- Drive Full-Stack Autonomy: Contribute to end-to-end systems that connect perception, semantic task understanding, and low-level robot control into a unified, reliable autonomy stack.
- Ship & Scale: Write, review, and maintain mission-critical Python and C++ code, continuously profiling and improving our stack for performance and reliability across our growing fleet.
- Education: PhD or MS in Robotics, CS, or related field with a track record of publications at CVPR, ICCV, ECCV, ICRA, or CoRL.
- Experience: 3+ years of hands-on experience shipping code for physical robots.
- Technical Expertise: Deep expertise in manipulation planning, imitation learning, and/or reinforcement learning.
- Engineering Excellence: Production-level proficiency in Python and C++ with a track record of building robust, maintainable systems.
- Familiarity with sim-to-real transfer and high-fidelity simulators (Isaac Lab, MuJoCo).
- Ownership: We offer a substantial equity package designed for those who believe in our mission and want to be rewarded for the company's long-term success.
- Impact: Work directly on real-world projects and see your code deployed in the real world immediately.
- Culture: A collaborative, high-velocity supportive environment conducive to both personal and professional growth.
Skills Required
- PhD or MS in Robotics, Computer Science, or related field with publications at CVPR, ICCV, ECCV, ICRA, or CoRL
- 3+ years hands-on experience shipping code for physical robots
- Deep expertise in manipulation planning, imitation learning, and/or reinforcement learning
- Production-level proficiency in Python and C++ with experience building robust, maintainable systems
- Familiarity with sim-to-real transfer and high-fidelity simulators (Isaac Lab, MuJoCo)
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The Company
What We Do
Autonomique is a Physical AI software company that develops a hardware-agnostic robotics intelligence framework. Its goal is to enable industrial robots to reason, plan, and execute complex manufacturing workflows with human-like adaptability and production-grade precision. The company focuses on high-demand industries such as automotive, aerospace, and electronics assembly, bridging the gap between lab demos and real-world industrial production.
