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Senior Reinforcement Learning Engineer(m/w/x)
Designing, training, and deploying reinforcement learning policies for legged robots in industrial plants. PhD or equivalent track record in RL and ML model deployment required. Attractive employee stock ownership plan.
Requirements
- PhD in robotics, machine learning, computer science, or related field with RL focus, or equivalent research/deployment track record
- Master's degree in robotics, machine learning, computer science, or related field from top-tier university
- Proven track record shipping and maintaining ML models
- Solid grounding in robot control fundamentals and autonomous systems
- Experience using robotic simulation tools (Gazebo, Isaac Sim)
- Strong understanding of sim-to-real transfer, domain randomization, reward shaping, policy robustness
- Proficiency in Python and PyTorch; working knowledge of C++
- Strong knowledge of Linux systems and middleware frameworks
- Pragmatic and solution-oriented mindset
- Excellent communication skills in English
- Experience training and deploying RL policies on physical robots
- Development of scalable and modular robot architectures
- Experience with navigation systems and autonomous mobile robot operation
- Interest in agentic engineering toolchains
- Experience leading software architecture design and best practices
- Solid grasp of physical systems (multibody dynamics, electromechanical drive physics, energy optimization, contact physics)
Tasks
- Lead design, training, and deployment of reinforcement learning policies
- Bridge simulation to real-world robot performance
- Provide senior technical guidance on RL and learning-based control
- Mentor engineers and establish best practices for policy development
- Own and evolve RL training infrastructure and sim-to-real pipeline
- Ensure reproducibility, scalability, and fast iteration cycles
- Shape technical vision for internal ML tooling and experiment management
- Drive efficiency and rigor in learning workflows
- Collaborate with cross-functional stakeholders to expand robot autonomy
- Triage field issues related to locomotion
- Identify and improve policy robustness based on deployment data
- Write, deploy, and maintain efficient Python and C++ software
Work Experience
- 5 years
Education
- Master's degree
Languages
- english – Native
Tools & Technologies
- Python
- PyTorch
- C++
- Linux
- Gazebo
- Isaac Sim
Benefits
Competitive Pay
- Attractive employee stock ownership plan
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Senior Reinforcement Learning Engineer(m/w/x)
Designing, training, and deploying reinforcement learning policies for legged robots in industrial plants. PhD or equivalent track record in RL and ML model deployment required. Attractive employee stock ownership plan.
Requirements
- PhD in robotics, machine learning, computer science, or related field with RL focus, or equivalent research/deployment track record
- Master's degree in robotics, machine learning, computer science, or related field from top-tier university
- Proven track record shipping and maintaining ML models
- Solid grounding in robot control fundamentals and autonomous systems
- Experience using robotic simulation tools (Gazebo, Isaac Sim)
- Strong understanding of sim-to-real transfer, domain randomization, reward shaping, policy robustness
- Proficiency in Python and PyTorch; working knowledge of C++
- Strong knowledge of Linux systems and middleware frameworks
- Pragmatic and solution-oriented mindset
- Excellent communication skills in English
- Experience training and deploying RL policies on physical robots
- Development of scalable and modular robot architectures
- Experience with navigation systems and autonomous mobile robot operation
- Interest in agentic engineering toolchains
- Experience leading software architecture design and best practices
- Solid grasp of physical systems (multibody dynamics, electromechanical drive physics, energy optimization, contact physics)
Tasks
- Lead design, training, and deployment of reinforcement learning policies
- Bridge simulation to real-world robot performance
- Provide senior technical guidance on RL and learning-based control
- Mentor engineers and establish best practices for policy development
- Own and evolve RL training infrastructure and sim-to-real pipeline
- Ensure reproducibility, scalability, and fast iteration cycles
- Shape technical vision for internal ML tooling and experiment management
- Drive efficiency and rigor in learning workflows
- Collaborate with cross-functional stakeholders to expand robot autonomy
- Triage field issues related to locomotion
- Identify and improve policy robustness based on deployment data
- Write, deploy, and maintain efficient Python and C++ software
Work Experience
- 5 years
Education
- Master's degree
Languages
- english – Native
Tools & Technologies
- Python
- PyTorch
- C++
- Linux
- Gazebo
- Isaac Sim
Benefits
Competitive Pay
- Attractive employee stock ownership plan
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
ANYbotics
Industry
Manufacturing
Description
ANYbotics is a fast-growing tech company dedicated to shaping the future of mobile robotics across multiple industries.
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