Senior Research Scientist | Multimodal Systems

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, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors. 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.

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.

Our Language AI teams form the foundation of DeepL's success. We are a dedicated group of researchers who collaborate closely with engineers, product managers, and designers. Our mission is to build the world's leading language AI system to deliver perfect translations for the most demanding use cases.

Your responsibilities include:

• Leading fine-tuning, post-training, and reinforcement learning for the next generation of DeepL's document translation multimodal and vision models.
• Driving the development of vision and multimodal models for document, image and media translation.
• Conducting hands-on research and development on post-training for our vision and/or multimodal models.
• Building evaluator models for document and design quality.
• Owning the full lifecycle of model delivery: prototyping, ablations, training, evaluation, optimization, and production deployment.
• Establishing strong practices for evaluation, reproducibility, monitoring, and continuous model improvement in production.

Qualities we look for:

• Proven experience with developing multimodal models, VLM, and/or vision models.
• Deep, hands-on expertise in model post-training, knowledge distillation, and/or reinforcement learning.
• Strong data-centric instincts for building synthetic-data and preference-data pipelines.
• A hands-on builder who enjoys training models, running experiments, and integrating ML systems into production.
• Strong coding and experimentation skills (Python, PyTorch/JAX/Tensorflow).
• Ability to lead complex research efforts and communicate clearly across teams.

Nice to have:

• Experience with machine translation, multilingual NLP, or multimodal machine translation.
• Experience designing evaluation and reward signals using automatic metrics.
• Experience with multi-objective optimization and diffusion models.
• Publications at top-tier venues.

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.