Hybrid Senior Staff Research Scientist

at DeepL

• Job title: Senior Staff Research Scientist
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Location requirements: Hybrid, Munich, Germany

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