Senior Staff Research Scientist in London

DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human‑like translation, improved writing and real‑time voice translation.

Foundation Model Team

We are the team behind DeepL’s post‑training stack for large language models, focusing on aligning pre‑trained models with tasks and performance goals through reinforcement learning and other techniques.

Responsibilities

• Shape scientific strategy and vision for post‑training across DeepL, identifying high‑leverage directions, setting technical standards and leading research initiatives.
• 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 and 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.

Qualifications

• 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 that span different teams.
• Strong expertise in deep reinforcement learning (RLHF, RLAIF, RLVR).
• Hands‑on experience scaling and deploying large language models 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

• Large, internationally distributed team with more than 90 nationalities.
• Open communication and regular feedback; a culture of empathy and growth mindset.
• Hybrid work schedule with flexible hours and trust in productivity.
• Monthly full‑day hacking sessions (Hack Fridays) to pursue passion projects.
• Thirty days of annual leave plus access to mental health resources.
• Competitive benefits tailored to each location.
• Virtual Shares – an ownership mindset for every employee.

We are an equal opportunity employer. We welcome applicants from all backgrounds and value authenticity. Our product is for everyone, and so is our workplace.