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Reinforcement Learning Intern(m/w/x)
Building end-to-end RL pipelines and prototyping control policy learning. Master's degree in CS, AI/ML, or related field required. International, diverse, equitable, and inclusive work environment.
Requirements
- Master's degree in Computer Science, AI/ML, Applied Mathematics, Control, or Engineering
- Foundations in reinforcement learning / sequential decision-making (MDPs, policy/value methods, offline RL or related areas)
- Solid programming skills (Python)
- Experimental mindset with hands-on coding, data handling, debugging experience
- Curiosity and motivation for RL and applied ML research
- English (professional working proficiency)
- French (plus)
Tasks
- Build end-to-end RL pipelines
- Prototype RL approaches for control policy learning
- Benchmark RL approaches for control policy learning
- Design exploration strategies
- Design reward functions
- Work with simulated environments
- Ensure methods translate beyond training setups
- Evaluate algorithms rigorously
- Perform ablations
- Perform sensitivity analyses
- Perform generalization tests
- Communicate findings to stakeholders
- Improve data/experiment workflows
- Improve dataset handling
- Improve experiment tracking
- Improve computing efficiency
- Stay close to current RL research
- Translate relevant RL ideas into applied solutions
Education
- Currently in higher education
Languages
- English – Business Fluent
- French – Basic
Tools & Technologies
- Python
- PyTorch
- TensorFlow
Benefits
Informal Culture
- International, diverse, equitable and inclusive work environment
Purpose-Driven Work
- Opportunities to have an impact
Learning & Development
- Endless learning opportunities
Other Benefits
- Enriching experiences
Mentorship & Coaching
- Strong mentorship
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Reinforcement Learning Intern(m/w/x)
Building end-to-end RL pipelines and prototyping control policy learning. Master's degree in CS, AI/ML, or related field required. International, diverse, equitable, and inclusive work environment.
Requirements
- Master's degree in Computer Science, AI/ML, Applied Mathematics, Control, or Engineering
- Foundations in reinforcement learning / sequential decision-making (MDPs, policy/value methods, offline RL or related areas)
- Solid programming skills (Python)
- Experimental mindset with hands-on coding, data handling, debugging experience
- Curiosity and motivation for RL and applied ML research
- English (professional working proficiency)
- French (plus)
Tasks
- Build end-to-end RL pipelines
- Prototype RL approaches for control policy learning
- Benchmark RL approaches for control policy learning
- Design exploration strategies
- Design reward functions
- Work with simulated environments
- Ensure methods translate beyond training setups
- Evaluate algorithms rigorously
- Perform ablations
- Perform sensitivity analyses
- Perform generalization tests
- Communicate findings to stakeholders
- Improve data/experiment workflows
- Improve dataset handling
- Improve experiment tracking
- Improve computing efficiency
- Stay close to current RL research
- Translate relevant RL ideas into applied solutions
Education
- Currently in higher education
Languages
- English – Business Fluent
- French – Basic
Tools & Technologies
- Python
- PyTorch
- TensorFlow
Benefits
Informal Culture
- International, diverse, equitable and inclusive work environment
Purpose-Driven Work
- Opportunities to have an impact
Learning & Development
- Endless learning opportunities
Other Benefits
- Enriching experiences
Mentorship & Coaching
- Strong mentorship
About the Company
Nestlé
Industry
Food
Description
Das Unternehmen ist führend in Ernährung, Gesundheit und Wellness und bietet Produkte für verschiedene Lebenssituationen an.
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