Data Engineer Intern — ML & MLOps (Paris)

Wiremind; Paris; Hybrid; EUR 10,000 - 13,000; Part time

Benefits offered by this job

Beautiful Paris office

1 day remote work per week

Attractive remuneration

WellPass access at preferential rate

Team culture and tech talks

Job summary

Wiremind Cargo is expanding its Data Engineering team in Paris for an end-of-study internship. You will join a cross-disciplinary department with devops, software and data engineering, data science, AIML, and operational research.

The role focuses on building robust data pipelines, implementing ML-driven features, and deploying models in production. The position offers a hybrid arrangement with one remote day per week, attractive remuneration, and a learning environment that supports growth

Qualifications

• Pursuing a Master's Degree in Engineering and seeking an end-of-study internship.
• Passionate about addressing business challenges through innovative technology solutions.
• Committed to high-quality standards in all work aspects.
• Solid understanding of computer science and eager to advance quickly with best development practices.

Responsibilities

• Support ML engineers by improving the MLOps platform.
• Work with software engineers to implement data science algorithms in client apps safely and scalably.
• Collaborate with the platform team to minimize infrastructure debt.
• Assist in deploying algorithms into production in a safe, scalable way.

Education

Master's Degree in Engineering

Tools

Python 3.11+

SQLAlchemy

Remoulade

FastAPI

Postgresql

Redis

Druid

Gitlab

Kubernetes

Prometheus

Grafana

Kibana

Job description

Wiremind Cargo is expanding its Data Engineering team in Paris for an end-of-study internship. You will join a cross-disciplinary department with devops, software and data engineering, data science, AIML, and operational research.

The role focuses on building robust data pipelines, implementing ML-driven features, and deploying models in production. The position offers a hybrid arrangement with one remote day per week, attractive remuneration, and a learning environment that supports growth