Internship September 2026, Ekimetrics
Agentic AI for Semi-Automating the Data Science Workflow
3+ days a week in office
Data science & AI for sustainable business performance
Be an early applicant
Data science & AI for sustainable business performance
201-500 employees
Be an early applicant
3+ days a week in office
201-500 employees
Company mission
To help companies get more from their data and implement pre-packaged AI solutions, so they can combine high impact with long-term business purpose.
Role
Who you are
- Currently in the final year of a Master's or Engineering degree, with strong foundations in machine learning, statistics, and programming
- Strong Python skills and experience with deep learning frameworks (PyTorch, TensorFlow); comfortable with the standard data science toolkit (pandas/polars, scikit-learn, gradient-boosting libraries)
- Familiarity with large language models and agentic techniques (prompting, tool/function calling, retrieval, multi-agent orchestration); hands-on experience with an agent framework is a plus
- Solid software engineering practices (version control, testing, clean code) and an interest in building reliable, scalable AI systems
- Exposure to Databricks, Spark, MLflow, or cloud data platforms is a plus
- Strong analytical and problem-solving skills, with the ability to work autonomously on an open-ended research-and-build problem
- Fluency in English
What the job involves
- This internship will focus on designing and building such a system: a multi-agent orchestration in which specialized agents (e.g. , feature engineering, modeling, evaluation) collaborate under a coordinating agent to produce runnable code that a data scientist reviews, refines, and merges
- The system is intentionally semi-automated: some steps run human-in-the-loop with explicit approval gates, while others run autonomously with human review of the output
- The intern will start with the feature engineering and modeling/experimentation loop, the part of the workflow where iteration is most intensive, and progressively extend coverage toward the end-to-end pipeline
- The work builds on recent state-of-the-art research in agentic data science, including AIDE [1], which frames machine learning engineering as a tree search over candidate code solutions; Data Interpreter [2], an end-to-end LLM agent that decomposes a data science task into a dynamic dependency graph; and AutoKaggle [3], a multi-agent pipeline whose phase-by-phase design and validated toolkit allow users to intervene at each stage, integrating automated intelligence with human expertise
- This internship offers an opportunity to engage with cutting-edge AI research and production engineering
- Conduct a focused literature review on agentic data science, automated machine learning, and LLM-agent techniques (planning, tool use, multi-agent orchestration), including human-in-the-loop and evaluation methods
- Contribute to the design of the multi-agent system and implement its components, starting with the feature engineering and modeling/experimentation loop and producing runnable notebooks/code for human review
- Participate in defining the human-in-the-loop interaction model (which steps run with explicit human approval versus autonomously with human review) and implement the corresponding control and guardrail logic
- Help integrate the system with the Databricks stack: governed data access via Unity Catalog, execution on Databricks compute, and experiment tracking, agent tracing, and evaluation via MLflow
- Support work on the safe and governed execution of agent-generated code, including isolation and access-control considerations
- Run experiments, evaluate prototypes on real-world datasets, and benchmark against prior art and MLE-bench-style task performance, iterating on architecture and prompts in collaboration with your N+1
- Share findings with the team and contribute to discussions on the long-term strategy for deploying agentic data science tooling in production
Application process
- 🔸Technical assessment on HackerRank
- 🔸HR interview with a Talent Acquisition Specialist
- 🔸Case study
- 🔸Final interview with a Manager
Our take
Making sense of data can help companies unlock incredible opportunities, but it can be difficult to maximise its rewards. Ekimetrics solves this problem by acting as a data consultant to companies and helping them to secure immediate business gains through data science and AI.
The company is active in numerous countries, owing its success in part to its ability to offer an "industrialised" data science experience. This has allowed it to onboard big-name partners such as Facebook, Google and Snap, firmly establishing itself as a leading force in the data science sector.
With its impressive funding and recognition, Ekimetrics has made a strong name for itself so far. It continues to expand internationally, introduce new products, and has completed its first acquisition with the purchase of AI customer analytics platform Actable.
Freddie
Company Specialist at Welcome to the Jungle
Insights
8% employee growth in 12 months
Company
Funding (1 round)
Nov 2020
$28m
GROWTH EQUITY VC
Total funding: $28m
Company benefits
- An emphasis on work-life-balance and 5 PTO days and holidays
- Close-knit team with friendly environment, bi-monthly team events and more
- Unique internal training package with 70+ sessions in our Eki.Academy digital platform
Company HQ
Faubourg-Montmartre, Paris, France
Leadership
Jean-Baptiste Bouzige
(CEO & Co-Founder)Previously worked as Business Planner at Eurostar, and as a Consultant at DDB Matrix.
Francois Poitrine
(GM & Co-Founder)Previously worked as a Business Developer at Heykom, and as a Consultant at DDB Matrix.
Paul Seguineau
(Global Deputy GM & Co-Founder)Previously worked as a consultant at Rapp Collins Paris.
Quentin Michard
(GM & Co-Founder)Previously worked as a PhD Research Associate at L'Oréal.
Salary benchmarks
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