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Postdoctoral Research Fellow studying molecular/epigenetic epidemiology at the University of Edinburgh. Engaging in research on biomarkers linked to organ ageing and disease outcomes, contributing to projects and collaborations.
About the role
- Senior Staff Research Scientist leading AI research and development at DeepL, shaping the future of model training while collaborating with cross-functional teams in an innovative environment.
Responsibilities
- Shape scientific strategy and vision for post-training across DeepL, identifying high-leverage directions, setting technical standards and leading research initiatives in a highly dynamic, fast-paced environment
- Build and deploy state-of-the-art reinforcement learning pipelines at scale
- Post-train large (multi-modal) models to align them with human intent and enable general capabilities such as reasoning, pushing the boundaries of model performance, safety, and efficiency
- Drive the entire lifecycle of research and production: from idea conception, theoretical modeling, prototyping, ablation studies, all the way to production deployment
- Work closely with cross-functional leadership to shape the technical strategy and priorities of the foundational models research track
- Build and foster external collaborations with academic and industrial partners
- Set scientific and technical standards for experimentation, reproducibility, and model evaluation
- Collaborate deeply with Engineering, ML Platform, and HPC teams to deliver robust and reliable model updates to users
- Mentor and guide senior scientists, researchers, and engineers, fostering a culture of excellence, curiosity, and impact
Requirements
- PhD (or equivalent experience) in Computer Science, Machine Learning, Applied Mathematics, Physics or a related field
- 5+ years of experience in ML research, including several years leading high-impact projects with responsibilities extending across different teams
- Strong expertise in deep reinforcement learning (RLHF/RLAIF/RLVR)
- Hands-on experience scaling and deploying LLMs or other foundation models in real-world systems
- Strong programming skills and experience working with large compute clusters and ML infrastructure
- Excellent communication skills — able to clearly explain complex topics to diverse audiences
- Track record of mentoring other scientists and setting technical long-term vision.
Benefits
- Competitive benefits
- Open, welcoming work culture
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Location requirements
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