Nomagic
Research Engineer(m/w/x)
Full-timeWith HomeofficeSenior
Zürich
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NONomagic
Research Scientist(m/w/x)
Zürich
Full-timeWith Home OfficeExperienced
AI/ML
Data Science
Nejo AI Summary
Designing multimodal model architectures for physical AI foundation models. Deep ML, systems engineering, and robotics experience required. Flexible working hours, relocation package.
Requirements
- Belief in physical AI through factory deployments
- Excitement for turning robotic stacks into physical AI training data
- Desire to bridge ML research and robotic execution
- Deep research and practical experience in ML, systems engineering, robotics
- Designing, training, fine-tuning large-scale deep learning architectures
- Strong deep learning framework fundamentals (PyTorch/JAX)
- Comfortable debugging at all stack layers
- Care for empirical rigor and iteration speed
- Hands-on hardware experience
- Understanding of robotics full stack (perception, controls, state estimation)
- Care for evaluation and failure analysis in physical world
- Ability to move between theoretical design and physical implementation
- Preference for execution, rapid iteration, real-world robustness
Tasks
- Design model architectures for multimodal robotic data
- Define training objectives and curricula for foundation models
- Develop scalable data mixtures and sampling strategies
- Run ablation studies to understand scaling laws and data quality
- Collaborate with ML Infra to optimize cluster utilization
- Explore fine-tuning methods for real-world adaptation
- Improve model controllability and safety using reinforcement learning
- Develop methods for real-world reliability and edge case handling
- Design evaluation frameworks for robot performance
- Analyze real-world evaluation results to guide research
- Bridge the gap between model outputs and physical outcomes
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- JAX
- VLMs
- VLAs
- RL
- RLHF
- Imitation Learning
Benefits
Flexible Working
- Flexible working hours
Informal Culture
- English-speaking environment
Additional Allowances
- Relocation package
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Nomagic 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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NONomagic
Research Scientist(m/w/x)
Zürich
Full-timeWith Home OfficeExperienced
AI/ML
Data Science
Nejo AI Summary
Designing multimodal model architectures for physical AI foundation models. Deep ML, systems engineering, and robotics experience required. Flexible working hours, relocation package.
Requirements
- Belief in physical AI through factory deployments
- Excitement for turning robotic stacks into physical AI training data
- Desire to bridge ML research and robotic execution
- Deep research and practical experience in ML, systems engineering, robotics
- Designing, training, fine-tuning large-scale deep learning architectures
- Strong deep learning framework fundamentals (PyTorch/JAX)
- Comfortable debugging at all stack layers
- Care for empirical rigor and iteration speed
- Hands-on hardware experience
- Understanding of robotics full stack (perception, controls, state estimation)
- Care for evaluation and failure analysis in physical world
- Ability to move between theoretical design and physical implementation
- Preference for execution, rapid iteration, real-world robustness
Tasks
- Design model architectures for multimodal robotic data
- Define training objectives and curricula for foundation models
- Develop scalable data mixtures and sampling strategies
- Run ablation studies to understand scaling laws and data quality
- Collaborate with ML Infra to optimize cluster utilization
- Explore fine-tuning methods for real-world adaptation
- Improve model controllability and safety using reinforcement learning
- Develop methods for real-world reliability and edge case handling
- Design evaluation frameworks for robot performance
- Analyze real-world evaluation results to guide research
- Bridge the gap between model outputs and physical outcomes
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- JAX
- VLMs
- VLAs
- RL
- RLHF
- Imitation Learning
Benefits
Flexible Working
- Flexible working hours
Informal Culture
- English-speaking environment
Additional Allowances
- Relocation package
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Nomagic 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
Nomagic
Industry
Research
Description
Nomagic is executing a pivot for general-purpose physical AI, leveraging robotics deployment logs to build foundational models for AI mastery.
Not a perfect match?
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