- Company Name
- Wiremind
- Job Title
- ML Engineer (M/F) - Internship - Paris
- Job Description
-
**Job Title**
ML Engineer Intern
**Role Summary**
Assisting in the design, training, evaluation, and operationalization of machine learning models for cargo demand forecasting and capacity optimization within a SaaS revenue‑management platform. Collaborate with senior ML engineers to enhance AI models and improve production pipelines.
**Expectations**
• 6‑month internship in a data‑science team focused on forecasting and optimization.
• Develop and refine models using state‑of‑the‑art algorithms; deliver interpretable, robust predictions.
• Work cross‑functionally with data and software engineering to ensure smooth model integration.
**Key Responsibilities**
1. Design, train, and fine‑tune supervised ML models (e.g., decision trees, deep neural networks) for time‑series demand forecasting.
2. Address imbalanced and skewed distributions; engineer features to improve model accuracy.
3. Conduct comprehensive model evaluation (accuracy, precision, recall, RMSE, etc.), track data drift, and propose improvement actions.
4. Contribute to the development and automation of the training pipeline (tests, CI/CD, data validation).
5. Review literature and current best practices to propose new modeling techniques or tooling improvements.
6. Participate in model versioning, registry (MLFlow), and monitoring (Prometheus/Grafana, Kibana).
**Required Skills**
- Proficiency in Python 3.11+ and data‑science libraries: Pandas, NumPy, Dask, LightGBM, XGBoost, TensorFlow/Keras, SHAP.
- Experience with SQLAlchemy, PostgreSQL, and data-warehouse concepts.
- Familiarity with version control (Git), CI/CD pipelines, and container orchestration (Kubernetes, Argo).
- Strong grasp of core ML concepts (classification, regression, time‑series), loss functions, regularization, evaluation metrics.
- Basic statistics knowledge and ability to interpret model outputs and predictive performance.
- Curiosity and motivation to learn new frameworks and research cutting‑edge methodologies.
**Required Education & Certifications**
- Currently enrolled in a Master’s program (or equivalent) in Data Science, Computer Science, Applied Mathematics, or related field.
- Demonstrated project or competition experience (e.g., Kaggle, university coursework) involving model development and deployment.
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