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# Machine Learning Engineer

- **Company:** JobTeaser
- **Location:** Paris, France (Remote available)
- **Experience:** Experienced
- **Salary:** €55,000.0 - €70,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Big Data, Business Software, Continuous Integration, Data Cleansing, DevOps, Python (Programming Language), Machine Learning, Azure Machine Learning, SQL Databases, Feature Engineering, Large Language Models, Containerization, Scikit Learn, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Xgboost, Machine Learning Operations, Software Version Control, Docker, Microservices
- **Published:** July 7, 2026
- **Apply:** https://jobs.smartrecruiters.com/JobTeaser/744000135987829-machine-learning-engineer-w-m-d-

## About the Role

* You hold a Master's degree (or equivalent) in Computer Science, Applied Mathematics, Data Science, or a related quantitative field.
 * You have 3 to 5 years of experience developing and deploying Machine Learning models in production environments.
 * You are proficient in Python and have hands-on experience with major ML/AI frameworks (scikit-learn, XGBoost, LightGBM, HuggingFace Transformers, DSPy…), we value practical experience and adaptability over specific tools.
 * You have solid knowledge of ML/LLMOps tools (MLflow, Kubeflow, DVC, DeepEval or similar) and ML-oriented DevOps practices.
 * You have experience with cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) and containerization (Docker, Kubernetes).
 * You are comfortable with SQL and knowledgeable in feature engineering and data preprocessing best practices.
 * You have a pragmatic, analytical, and results-oriented mindset: you favor frequent iterative deliveries over long research tunnels.
 * You enjoy working in cross-functional teams (Data, Tech, Product) and can translate business needs into concrete ML/AI solutions.
 * You are autonomous, curious, and comfortable in a fast-evolving ecosystem.
 * Professional proficiency in English, bilingual in French.

## Description

* Design, develop, and deploy end-to-end ML and AI pipelines, from problem framing and experimentation through to production.
 * Build and maintain robust data and ML pipelines for model training, evaluation, and deployment, develop LLM-powered features including RAG, structured prompting, few-shot learning, and OCR integration.
 * Implement and evolve ML/LLMOps practices: model versioning, production monitoring, reproducibility, and continuous improvement.
 * Develop APIs and microservices to expose ML/AI models to business applications.
 * Analyze large datasets, identify modeling challenges, propose solutions, and iterate quickly.
 * Collaborate closely with Data, Product, and Engineering teams to turn prototypes into scalable, reliable production solutions.
 * Stay current on academic and industrial advances in Machine Learning, LLMs and emerging AI technologies and apply them to real-world use cases.
 * Contribute to best practices in testing, CI/CD, and deployment automation.


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