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- Tasks: Lead cutting-edge research in reinforcement learning and deploy state-of-the-art models.
- Company: Join DeepL, a global leader in Language AI transforming communications.
- Benefits: Enjoy 30 days annual leave, hybrid work, and competitive benefits tailored to you.
- Why this job: Make a real impact in AI while mentoring the next generation of scientists.
- Qualifications: PhD in relevant field and 5+ years of ML research experience required.
- Other info: Collaborative culture with diverse teams and monthly Hack Fridays for passion projects.
The predicted salary is between 48000 - 72000 ÂŁ per year.
DeepL is a global communications platform powered by Language AI. Since 2017, we’ve been on a mission to break down language barriers and enable over 100,000 businesses to transform communications. Our human‑sounding translations and intelligent writing suggestions are designed with enterprise security in mind.
About the Team
We are the Foundation Model Task Adaptation team – tackling the post‑training stack for large language models. Our focus is on aligning pretrained models with tasks and performance goals using reinforcement learning and other advanced techniques.
Responsibilities
- Lead the design, implementation, and deployment of cutting‑edge research in reinforcement learning and post‑training at scale.
- Define DeepL’s scientific direction in this area and mentor researchers.
- Build and deploy state‑of‑the‑art reinforcement learning pipelines at scale.
- Post‑train large (multi‑modal) models to align with human intent and enable capabilities such as reasoning.
- Drive the entire lifecycle of research and production from concept to production deployment.
- Collaborate with cross‑functional leadership to shape technical strategy and priorities.
- Build external collaborations with academic and industrial partners.
- Set scientific and technical standards for experimentation, reproducibility, and model evaluation.
- Collaborate with Engineering, ML Platform, and HPC teams to deliver robust model updates.
- Mentor and guide senior scientists, researchers, and engineers.
Qualifications
- PhD (or equivalent) in Computer Science, Machine Learning, Applied Mathematics, Physics, or related field.
- 5+ years of ML research experience, including leading high‑impact projects.
- Strong expertise in deep reinforcement learning (RLHF/RLAIF/RLVR).
- Hands‑on experience scaling and deploying LLMs or foundation models in real‑world systems.
- Strong programming skills and experience with large compute clusters and ML infrastructure.
- Excellent communication skills – able to explain complex topics to diverse audiences.
- Track record of mentoring other scientists and setting long‑term technical vision.
Benefits & Culture
- Diverse, globally distributed team with over 90 nationalities.
- Open communication, regular feedback, and empathy‑driven culture.
- Hybrid work schedule – team members in the office twice a week with flexible hours.
- Monthly full‑day hacking sessions (Hack Fridays) for passion projects.
- 30 days of annual leave (excluding public holidays) and mental health resources.
- Competitive benefits tailored to each location.
- Virtual Shares – every employee receives virtual shares linking your contribution to DeepL’s growth.
Equal Opportunity Statement
We are an equal‑opportunity employer. Your background, experience, and perspective matter. We value authenticity and diversity and strive to break language barriers together.
Senior Staff Research Scientist in London employer: DeepL
Contact Detail:
DeepL Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Staff Research Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in your field, attend industry events, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your expertise in reinforcement learning and model deployment. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. We love seeing real-world applications of your skills, especially when it comes to large language models and innovative research.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals who want to break down language barriers with us.
We think you need these skills to ace Senior Staff Research Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Staff Research Scientist role. Highlight your expertise in reinforcement learning and any relevant projects you've led. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background fits with our team’s goals. Don’t forget to mention any experience with large language models or mentoring others.
Showcase Your Projects: If you've worked on any high-impact ML projects, make sure to include them in your application. We love seeing real-world applications of your skills, especially those involving deep reinforcement learning or model deployment.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at DeepL
✨Know Your Stuff
Make sure you brush up on the latest advancements in reinforcement learning and large language models. Be ready to discuss your past projects and how they align with the responsibilities of the role. This shows you're not just familiar with the theory but have practical experience too.
✨Showcase Your Leadership Skills
Since this role involves mentoring and guiding other scientists, be prepared to share examples of how you've led teams or projects in the past. Highlight your ability to set a long-term technical vision and how you've successfully collaborated with cross-functional teams.
✨Communicate Clearly
You’ll need to explain complex topics to diverse audiences, so practice articulating your ideas clearly and concisely. Use examples from your experience to illustrate your points, and don’t shy away from simplifying jargon when necessary.
✨Ask Insightful Questions
Prepare thoughtful questions about DeepL’s scientific direction and the Foundation Model Task Adaptation team. This not only shows your genuine interest in the role but also helps you gauge if the company culture and goals align with your own.
