At a Glance
- Tasks: Design and implement cutting-edge research in reinforcement learning and model alignment.
- Company: Join DeepL, a global leader in AI technology and innovation.
- Benefits: Enjoy flexible hours, hybrid work, 30 days annual leave, and competitive benefits.
- Other info: Be part of a diverse team with a shared mission to connect cultures.
- Why this job: Shape the future of AI while making a real-world impact.
- Qualifications: Strong background in mathematics, computer science, and practical experience in machine learning.
Meet DeepL. 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.
Founded in 2017 by CEO Jaroslaw "Jarek" Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures. Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey.
What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We're a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected.
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 Senior Research Scientist, you'll design, implement, and deploy cutting-edge research in reinforcement learning and post-training at scale, driving innovations that make it into production. You will:
- 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.
- Always keep the entire lifecycle of research and production in mind: from idea conception, theoretical modeling, prototyping, ablation studies, all the way to production deployment.
- Build and foster external collaborations with academic and industrial partners.
- Follow 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.
Qualities we look for: We're looking 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. We are seeking researchers with a strong practical background, a creative mindset, and a passion for solving hard problems with real-world impact. You have 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.
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: as a language-focused company, 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 three times 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 it to reflect the diversity of our team and tailored it to align with your unique location.
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.
Senior Research Scientist FMTA employer: DeepL SE
DeepL is an exceptional employer that fosters a dynamic and inclusive work culture, where innovation thrives and employees are empowered to lead impactful projects. With a strong focus on professional development, the company offers ample growth opportunities and a hybrid work model that promotes work-life balance, making it an ideal place for those looking to make a meaningful contribution in the fast-evolving field of AI and payments.
StudySmarter Expert Advice🤫
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We think you need these skills to ace Senior Research Scientist FMTA
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at DeepL SE. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
