Data Science Researcher – MLLMs

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Your Strategic Partner in Building World-Class Data & Tech Teams | Co-founder at Dataworks

Data Science Researcher – MLLMs

Location: France (Remote or Hybrid in Paris)

A fast-growing AI startup (Series B) in the retail industry is expanding its research capabilities and looking for an experienced Data Science Researcher to push the boundaries of Multimodal Large Language Models (MLLMs) and model reasoning . If you are passionate about LLMs for images (and videos as a plus) and want to work on cutting-edge AI research with real-world impact, this role is for you!

ABOUT THE ROLE

You will join a highly collaborative research and data science team (10+ people) , working closely with the Head of Data and Chief Scientific Officer to explore and advance AI-driven capabilities. Your work will directly contribute to building next-generation AI models for real-world applications.

Your responsibilities will include:

1. Researching and developing new methodologies in MLLMs, model reasoning, and multimodal AI (image & video understanding)
2. Exploring advanced architectures to improve reasoning and interpretability of large-scale models
3. Running experiments, prototyping POCs , and pushing research into production
4. Staying at the cutting edge of AI by keeping up with recent papers, conferences, and best practices in deep learning and LLMs
5. Collaborating with engineers and data scientists to bring research breakthroughs into scalable AI products

SKILLS & EXPERIENCE

1. Master’s or PhD in Computer Science, Machine Learning, AI, Mathematics, or a related field
2. Strong programming skills in Python (PyTorch/TensorFlow experience preferred)
3. Deep understanding of LLMs, MLLMs, and reasoning models (image-focused, video experience is a plus)
4. Experience with data pipelines, model evaluation, and optimization
5. A startup mindset – adaptable, curious, and a great team player!

Seniority level

• Associate

Employment type

• Full-time

Job function

• Information Technology, Engineering, and Science

Industries

• Data Infrastructure and Analytics, Technology, Information and Media, and Retail

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