Research Scientist in London

Meet DeepL. DeepL is a global communications platform powered by Language AI. Since 2017, we have been on a mission to break down language barriers. Our human-sounding translations and intelligent writing suggestions are designed with enterprise security in mind. Today, they enable over 100,000 businesses to transform communications, reach new markets, and improve productivity. Our goal is to become the global leader in Language AI, building products that drive better communication, foster connections, and make a real-life impact.

What sets us apart is our blend of modern technology, competitive benefits, and an open, welcoming work culture that enables our people to thrive. When we share what it’s like to work at DeepL, the reactions are overwhelmingly positive. This may be because of our products that have helped countless people worldwide or our shared mission to improve communication for individuals and businesses, bringing cultures closer together. What we know for sure is this: being part of DeepL means joining a team dedicated to innovation and employee well-being.

Research Scientist - FMTAMeet the team behind this journey: Foundation Model Task Adaptation. We are the team behind DeepL's post-training stack for large language models. We focus on developing algorithms and systems that align pre-trained models with tasks and performance goals through techniques like reinforcement learning. As a research-driven team, we stay up to date with current literature to integrate cutting-edge ideas into our core stack. As part of this team, you will shape the future of how our models learn beyond pre-training: enabling new capabilities, better controllability, and safer, more effective user experiences.

Your responsibilities as a Research Scientist include:

• Designing, implementing, and deploying cutting-edge research in reinforcement learning and post-training at scale, driving innovations that make it into production.
• Building and deploying state-of-the-art reinforcement learning pipelines at scale.
• Post-training 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.
• Keeping the entire lifecycle of research and production in mind: from idea conception, theoretical modeling, prototyping, ablation studies, all the way to production deployment.
• Building and fostering external collaborations with academic and industrial partners.
• Following scientific and technical standards for experimentation, reproducibility, and model evaluation.
• Collaborating deeply with Engineering, ML Platform, and HPC teams to deliver robust and reliable model updates to users.

Qualities we look for:

• A scientist with a deep technical background, strong leadership skills, and a proven track record of driving research in reinforcement learning or large-scale model alignment to production.
• Researchers with a strong practical background, a creative mindset, and a passion for solving hard problems with real-world impact.
• A solid mathematical background and enjoy solving challenging problems, evidenced by a master's degree, diploma, PhD, or equivalent industry experience in mathematics, physics, computer science, or a related field.
• Deep practical experience in Python and at least one modern machine learning framework such as PyTorch, TensorFlow, or JAX; experience working with large compute clusters and ML infrastructure is a plus.
• A track record of leading self-directed research projects that go well beyond academic exercises and deliver tangible results.
• Expertise in deep reinforcement learning (RLHF/RLAIF/RLVR) is a plus.
• Hands-on experience scaling and deploying LLMs or other foundation models in real-world systems is a plus.

What we offer:

• Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities.
• Open communication, regular feedback: we value the importance of clear, honest communication.
• Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week.
• Monthly full-day hacking sessions: every month, we have Hack Fridays, where you can spend your time diving into a project you’re passionate about.
• 30 days of annual leave: we value your peace of mind.
• Competitive benefits: we’ve crafted our benefits package to reflect the diversity of our team.
• Virtual Shares: every employee receives Virtual Shares, linking your contribution directly to DeepL's growth.

If this role and our mission resonate with you, but you’re hesitant because you don’t check all the boxes, don’t let that hold you back. At DeepL, it’s all about the value you bring and the growth we can foster together. Go ahead, apply—let’s discover your potential together. We can’t wait to meet you.

We are an equal opportunity employer. You are welcome at DeepL for who you are—we appreciate authenticity here. Our product is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all succeed, contribute, and think forward.