INTERNSHIP - Data engineering & AI-ready software architecture

Lesaffre; Marcq-en-Barœul; On-site; EUR 12,000 - 17,000; Full time

Benefits offered by this job

Ambiance internationale

Environnement enrichissant

Job summary

Lesaffre, acteur majeur de la fermentation, offre un stage de 6 mois à Marcq-en-Barœul, au croisement de la R&D NMH et de Biodata.

Vous concevrez une interface web Streamlit en Python pour transformer les sorties d’instruments en résultats propres et interrogeables par des IA, avec des pipelines et tests.

Le poste exige un bon niveau d’anglais, une formation en informatique et une curiosité pour la microbiologie; vous collaborerez avec des biologistes et des ingénieurs en bioinformatique.

Qualifications

• Actuellement en Master 2 ou dernière année d'école d'ingénieurs.
• Autorisation de travail en France.
• Majeure informatique, génie logiciel ou data engineering.
• Maîtrise de Python et concepts de software engineering.
• Connaissances en Git, Docker et TF (TensorFlow).

Responsibilities

• Concevoir des modules d'extraction automatisée des données expérimentales.
• Standardiser les schémas de données et assurer traçabilité et qualité.
• Structurer les datasets et développer des outils/endpoints pour query et analyse.
• Expose des services via REST et créer des interfaces (Streamlit).
• Appliquer les bonnes pratiques CI/CD et documentation technique.

Skills

Python

Git

Docker

LLM intégration

Bioinformatique

Education

Master 2 ou dernière année ingénierie

Tools

Docker

TensorFlow

JSON schemas

Job description

• Full-time
• Years of experience: Graduate
• Activity: Corporate
• Contract type: Internship - Stage

Company Description

Major global fermentation player for more than a century, Lesaffre, with more than 3 billion euros in revenue, has a presence on all continents, with 11,000 employees from over 90 nationalities. Using our expertise and diversity, we collaborate with clients, partners, and scientists to find increasingly relevant responses to the needs of nutrition, health, naturalness, and respect for our environment. Thus, every day, we explore and reveal the infinite potential of microorganisms.

Feeding 9 billion people in 2050 in a healthy way while using the planet's resources in the most efficient manner is a major and unprecedented challenge. We believe that fermentation is one of the most promising answers to this challenge.

Lesaffre - Working together to better nourish and protect theplanet.

Lesaffre is a leader in bioengineering & bioprocesses and places RD&I at the heart of its success: more than 850 experts worldwide explore the potential of microorganisms and natural fermentation to serve human, plant, and animal needs.

You will join this research community at the interface of two RD&I teams: NMH (Nutrition, Microbiota & Health), which runs experimental science (microbiological assays, imaging, microbiota work), and Biodata, focusing on data science and bioinformatics team that builds the computational tools used by our scientists. You will be co-mentored by an NMH Scientist and a BioData DevOps engineer.

Job Description

The scientific problem

Every week, NMH experiments produce large volumes of heterogeneous measurements: plate-reader kinetics, microbiological assay readouts, imaging data, each in the native format of the instrument that produced it. Today, turning that raw output into an analysable result is largely manual:

• Experimental time is lost to data wrangling rather than to designing and running the next experiment.
• Results are hard to compare across campaigns, because the same biological variable is recorded differently depending on the instrument, the operator, and the date.
• Reprocessing a past experiment is difficult, which limits reproducibility and prevents the accumulated data from being reused to generate new hypotheses.

Internship goal: build a web interface in streamlit, python layer that takes raw instrument output to a clean, described, queryable experimental result and make that result directly consumable by modern AI architectures (LLMs, RAG pipelines, autonomous agents), so that a scientist can interrogate their own data in natural language.

Key responsibilities

• Instrument data acquisition & parsing: Design automated extraction modules capable of ingesting raw experimental data streams from various laboratory instruments and heterogeneous file formats, ensuring cleaning, typing, and quality control.
• Data standardization & schema modeling: Define and implement strict, unified data schemas (metadata, type validation, JSON serialization formats) to ensure data interoperability and reproducibility.
• Architecture: Structure datasets and develop tools/function calling endpoints, enabling AI agents or LLM/RAG pipelines to autonomously query, analyze, and manipulate standardized datasets.
• API & internal tooling: Expose processing services via REST APIs and build lightweight interfaces (e.g., Streamlit) enabling scientific teams to visualize, validate, and query data independently.
• Apply Biodata’s software engineering best practices: containerization (Docker), version control (Git), unit/integration testing, and technical documentation.

By the end of the internship you will deliver a deployed, operational standardization pipeline for at least one NMH data family; a documented experimental data schema; an LLM‑queryable access layer; and a lightweight interface used by the scientific team. Success will be demonstrated via a live demo, automated tests, deployment instructions, a short technical report, and readiness for inclusion in the supported scientific campaign.

Qualifications

Education

• Currently enrolled in a Master 2 or final year of Engineering School at a French university or higher French education institution (mandatory for the internship agreement / convention de stage).
• Must already hold valid authorization to work in France.
• Major in Computer Science, Software Engineering or Data Engineering.

Skills

Technical:

• Languages & data processing: advanced Python proficiency.
• Software engineering: Git, environment management, containerization concepts (Docker, TF).
• AI & data integration: data indexing concepts, databases, and LLM/agent integration patterns (function calling, JSON schemas).
• Appreciated: handling scientific and tabular data (units, dilutions, replicates, plate formats, time series), and any exposure to bioinformatics or laboratory data.

Mindset & interpersonal:

• Computer science / software engineering background. No prior biology background is required the scientific context will be provided by the research teams but genuine curiosity for microbiology and fermentation is expected: you will be modelling biological experiments, not generic records.
• Rigorous approach, strong abstraction skills, and commitment to code quality (Clean Code).
• Strong interpersonal skills for a multidisciplinary environment: you will sit with biologists and microbiota experts, understand how an experiment is carried out, and translate that into technical specifications

Languages: fluent English (written and spoken)

Additional Information

Desired starting date on January 2027, for a 6-months internship.

[Benefits of Joining Lesaffre]:

• Join a family business rich in a long history with human-oriented values with a mission: To Nourish and Protect our Planet,
• Evolve in an enriching work environment and a multicultural context

[Diversity & Inclusion]: At Lesaffre, diversity is a strength that enriches our culture and our teams. We are committed to offering you a work environment where you can thrive, regardless of your background, gender, age or abilities. We encourage all applications, as we believe that diverse perspectives strengthen our ability to innovate and meet the challenges of tomorrow.