Flexion Robotics
Research Engineer - Dexterous Manipulation (Egocentric Models)(m/w/x)
Full-timeOn-siteSenior
Zürich
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FLFlexion Robotics
.AI Research Engineer - RL Manipulation(m/w/x)
Zürich
Full-timeOn-siteExperienced
AI/ML
Nejo AI Summary
Developing RL algorithms for humanoid robot manipulation, closing sim-to-real gaps. MSc or PhD in Robotics/ML with RL and manipulation focus required. Energetic, collaborative team environment.
Requirements
- MSc or PhD in Robotics, Machine Learning, or related field
- Strong focus on reinforcement learning and manipulation
- Experience with robot manipulation problems
- Experience with contact-rich or dexterous tasks
- Strong background in reinforcement learning
- Experience with modern reinforcement learning algorithms
- Awareness of practical limitations of reinforcement learning
- Hands-on experience with sim-to-real transfer
- Excellent programming skills in Python
- Ability to operate independently
- Ability to push open-ended problems to completion
Tasks
- Develop new algorithms for RL-based manipulation
- Scale training systems for efficient learning
- Close the loop between simulation and real-world performance
- Tackle sparse rewards and exploration challenges
- Improve sim-to-real transfer through better modeling
- Enhance training strategies and use real-world data
- Design learning-based approaches for complex tasks
- Focus on dexterous and contact-rich interactions
- Target real-world humanoid capabilities
- Solve multi-stage manipulation problems with delayed rewards
- Address credit assignment and stability challenges
- Develop methods for reliable policy transfer
- Improve robustness and handle model mismatch
- Leverage domain randomization and system identification
- Optimize large-scale training pipelines
- Increase simulation throughput for complex behaviors
- Explore novel learning methods
- Integrate reinforcement learning with imitation learning
- Collaborate with simulation and control teams
- Ensure tight integration between algorithms and infrastructure
Work Experience
- approx. 1 - 4 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Robotics
- Machine Learning
- Reinforcement Learning
Benefits
Competitive Pay
- Competitive compensation package
Informal Culture
- Energetic, collaborative team
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Flexion Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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FLFlexion Robotics
.AI Research Engineer - RL Manipulation(m/w/x)
Zürich
Full-timeOn-siteExperienced
AI/ML
Nejo AI Summary
Developing RL algorithms for humanoid robot manipulation, closing sim-to-real gaps. MSc or PhD in Robotics/ML with RL and manipulation focus required. Energetic, collaborative team environment.
Requirements
- MSc or PhD in Robotics, Machine Learning, or related field
- Strong focus on reinforcement learning and manipulation
- Experience with robot manipulation problems
- Experience with contact-rich or dexterous tasks
- Strong background in reinforcement learning
- Experience with modern reinforcement learning algorithms
- Awareness of practical limitations of reinforcement learning
- Hands-on experience with sim-to-real transfer
- Excellent programming skills in Python
- Ability to operate independently
- Ability to push open-ended problems to completion
Tasks
- Develop new algorithms for RL-based manipulation
- Scale training systems for efficient learning
- Close the loop between simulation and real-world performance
- Tackle sparse rewards and exploration challenges
- Improve sim-to-real transfer through better modeling
- Enhance training strategies and use real-world data
- Design learning-based approaches for complex tasks
- Focus on dexterous and contact-rich interactions
- Target real-world humanoid capabilities
- Solve multi-stage manipulation problems with delayed rewards
- Address credit assignment and stability challenges
- Develop methods for reliable policy transfer
- Improve robustness and handle model mismatch
- Leverage domain randomization and system identification
- Optimize large-scale training pipelines
- Increase simulation throughput for complex behaviors
- Explore novel learning methods
- Integrate reinforcement learning with imitation learning
- Collaborate with simulation and control teams
- Ensure tight integration between algorithms and infrastructure
Work Experience
- approx. 1 - 4 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Robotics
- Machine Learning
- Reinforcement Learning
Benefits
Competitive Pay
- Competitive compensation package
Informal Culture
- Energetic, collaborative team
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Flexion Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Flexion Robotics
Industry
IT
Description
Flexion builds the intelligence layer for next-gen humanoid robots, accelerating their real-world deployment.
Not a perfect match?
- Flexion Robotics
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