Data engineering & AI-ready software architecture Intern

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.

Expected deliverables

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.
• Architectures & APIs: REST API design.
• 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.