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Stage 2027 AI/ML Engineer 100% R&D - Tabular foundation modelsEkimetrics · Paris

Ekimetrics

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Stage 2027 AI/ML Engineer 100% R&D - Tabular foundation models

🗓️ Posted 2026-10-21 Paris Internship Hybrid ICT
💰 Salary Not shared 📊 Market 2,800 EUR–3,800 EUR/mo

About the Company

nalytical capital, and deploy actionable solutions that maximize their marketing and operational performance while reinvigorating business models. Our absolute focus is on delivering short-term gains while ensuring the long-term development of our clients' data capital. We are committed to offering the most advanced data science approaches and building ethical, sustainable AI practices. Key Figures 20 years of experience in data science 500+ data scientists, all consultants 5 offices in Paris, London, New York, Hong Kong, and Shanghai 350+ clients (CAC40, Fortune500) 1M+ in profit generated for our clients since 2006 1,000+ data science projects Within Ekimetrics, the Innovation Department works on AI research topics in collaboration with our industrial and academic partners. The department comprises several PhD experts in generative AI, deep learning, computer vision, time series, explainability, and causality. Each expert leads teams tasked with studying and building state-of-the-art methods and adapting them to specific business problems, developing new methodologies or algorithms to address identified challenges, and ensuring a seamless handover for integration within Ekimetrics' industrial ecosystem. A central focus of the Innovation Department is closing the gap between cutting-edge AI agents and the day-to-day reality of deliverin

Responsibilities

  • ● The intern will:
  • ● Review the literature on latent reasoning (NLP) and tabular foundation models, building on recent surveys.
  • ● Identify and adapt latent reasoning mechanisms to TFM architectures (e.g. iterative depth-wise computation, hidden-state reuse).
  • ● Implement them on open-source TFMs and measure their effect on accuracy, calibration and robustness against strong baselines (gradient boosting, standard TFMs) at comparable compute.
  • ● Apply interpretability methods (representation analysis, probing, activation patching) to characterize the computation performed during latent reasoning.
  • ● Build an evaluation protocol on diverse tabular datasets, including realistic business cases.
  • ● Document the results and contribute to scientific publications.
  • ● Currently in the final year of a Master's or Engineering degree, with strong foundations in machine learning, statistics, and programming.
  • ● Good grasp of model validation: train/test splits, data leakage, baselines.
  • ● Strong analytical skills and the ability to work autonomously on an open-ended research problem.
  • ● Knowledge of transformers and language models; familiarity with latent reasoning or recurrent-depth models is a plus.
  • ● Strong Python and PyTorch skills, and a solid command of the standard data science toolkit (pandas/polars, scikit-learn, gradient-boosting libraries).
  • ● Fluency in English is a plus.
  • ● Nice to have: experience in interpretability, knowledge of TabPFN, TabICL or TabDPT, and solid software engineering practices (git, code review, testing).

Benefits

  • ● Hands-on Research & Engineering Experience: Build a pioneering agentic system on real data science workflows, contributing to a tool with direct real-world impact.
  • ● Collaborative Learning: Engage with a team of data scientists, AI experts, and PhDs in a dynamic, research-driven environment within Ekimetrics' Innovation Department.
  • ● Skill Development: Gain expertise in LLM agents, the evaluation of AI systems, and production tooling on Databricks (Unity Catalog, MLflow).
  • ● Career Growth: Opportunity to transition into a full-time Data Scientist role in AI at Ekimetrics, or into a PhD program, upon successful completion of the internship.
  • ● Scientific Contribution: Opportunity to co-author and publish scientific papers in reputable AI and data science conferences and journals.
  • ● Networking: Collaborate with Ekimetrics' industrial and academic partners, enhancing your professional network in the AI research community.
  • ● Ethical and Sustainable AI: Learn to develop AI solutions that align with ethical, governed, and sustainable best practices, a core commitment of Ekimetrics.
  • ● Duration: 6 months, Paris
  • ● 1 Zhu, R.-J. et al. (2025). A Survey on Latent Reasoning. arXiv:2507.06203.
  • ● 2 Chen, X. et al. (2025). Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning. arXiv:2505.16782.
  • ● 3 Tabular Foundation Models: A Systematic Survey. authors, year, link to complete
  • ● 4 Biloš, M. et al. (2026). A Mechanistic Study of Tabular Foundation Models. link to complete