Research Scientist – FMTA
DeepL
full-time
Posted on:
Location Type: Hybrid
Location: Berlin • Germany
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Tech Stack
About the role
- Design, implement, and deploy cutting-edge research in reinforcement learning and post-training at scale
- Build and deploy state-of-the-art reinforcement learning pipelines at scale
- Post-train large (multi-modal) models to align them with human intent
- Collaborate deeply with Engineering, ML Platform, and HPC teams
Requirements
- A solid mathematical background
- Deep practical experience in Python
- Experience with at least one modern machine learning framework such as PyTorch, TensorFlow, or JAX
- A track record of leading self-directed research projects
- Expertise in deep reinforcement learning (RLHF/RLAIF/RLVR) is a plus
- Hands-on experience scaling and deploying LLMs or other foundation models is a plus
Benefits
- Diverse and internationally distributed team
- Open communication, regular feedback
- Hybrid work, flexible hours
- Monthly full-day hacking sessions
- 30 days of annual leave
- Competitive benefits
- Virtual Shares
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Pythonreinforcement learningdeep reinforcement learningPyTorchTensorFlowJAXscaling modelsdeploying modelspost-traininglarge language models
Soft skills
collaborationleadershipself-directed research