Robotics Engineer - Robot Learning
Who We Are
At Athenyx Robotics, we are building the intelligence stack for industrial humanoid robotics.
Our goal is to enable robots to move beyond rigid automation towards adaptive, learning-based systems that can operate across real-world industrial environments. We combine advances in robot learning, perception, and simulation with direct access to industrial use cases, data, and systems.
We are not building isolated demos - we are developing a platform for AI-native robotics, where perception, reasoning, and action are tightly integrated. Working closely with industry partners and research ecosystems, we bring cutting-edge methods into real-world deployment.
Overview
We are seeking a Robotics Engineer focusing on Robot Learning to develop learning-based approaches for robotic systems operating in complex, real-world environments.
You will work at the intersection of learning, simulation, and real-world deployment, contributing to systems that move beyond scripted automation towards adaptive and generalizable behavior.
As part of an early team, you are expected to operate with a T-shaped profile: deep expertise in one area, combined with the ability and willingness to contribute across the full robotics stack.
Your Responsibilities
Learning, Policies & Behavior
- Develop and train learning-based control policies using approaches such as imitation learning, reinforcement learning, and behavior modeling
- Design and implement end-to-end and modular policy architectures for tasks like manipulation, handling, and inspection, with a strong focus on generalization
- Contribute to behavior and skill modeling, including skill abstraction, composition, and policy conditioning
Simulation, Integration & Deployment
- Train and evaluate models in simulation environments and bridge simulation and real-world deployment (Sim2Real)
- Collaborate closely with perception and robotics engineers to build end-to-end systems integrating sensing, reasoning, and action
- Support integration, testing, and deployment on real robotic systems in industrial environments
What You Bring
- Degree (Bachelor, Master, or PhD) in robotics, computer science, machine learning, or a related field, with a strong foundation in robot learning, control, or learning-based behavior modeling
- Strong programming skills in Python and experience with modern ML and robotics workflows, such as training models, working in simulation, or integrating systems
- Experience in areas such as reinforcement learning, imitation learning, policy learning, or emerging approaches like generalist policies, foundation models, or world modeling
- Interest in real-world robotic systems and motivation to go beyond isolated components, from algorithm design to deployment on physical systems
- Willingness to work across the stack in a small team, taking ownership and supporting wherever needed
Nice to Have
- Experience with simulation environments and Sim2Real transfer
- Familiarity with perception pipelines (e.g. 3D vision, pose estimation)
- Experience with manipulation or contact-rich interaction
What We Offer
- Work on real robotic systems in industrial environments with direct impact on how robotics is deployed in practice
- Close collaboration with industry partners and access to real-world use cases, data, and systems
- High ownership and responsibility from day one in a small, highly capable, and execution-focused team
- Flexible working hours and an open, collaborative culture with a strong focus on building and learning
- The opportunity to help shape a new generation of AI-driven robotics systems from the ground up