Machine Learning Engineer - PRISM - Supply Chain (f/m/d)
HybridParis, Île-de-France, France
Job Summary
Develop and implement AI models for demand and assortment planning in the supply chain domain, collaborating with Data Scientists and Digital Product Managers to translate business requirements into scalable solutions. Industrialize machine learning models by deploying them into production environments using Databricks, AWS EKS, and Sagemaker, while optimizing data pipelines to ensure timely availability of clean data. Monitor model performance, implement retraining strategies, and document best practices for deployment processes. Provide mentorship to junior team members and stay updated on emerging trends in machine learning and supply chain optimization. Work remotely two days per week with flexibility in work organization.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- 5 years of experience in machine learning engineering or a similar role
- Demonstrated experience in developing and deploying machine learning models
- Proficiency in machine learning techniques, particularly Time Series Forecasting
- Strong programming skills in Python
- Experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, or scikit-learn
- Familiarity with data engineering concepts and tools for data preprocessing, feature engineering, and model evaluation
- Familiarity with industrializing and deploying machine learning models in production environments (MLOps, Containerization, orchestration, CI/CD, Infrastructure as Code, Monitoring and Logging, Scalability and Performance Optimization, Interfacing, parallelization, gpu computing, automatic backtesting...)
Desired Qualifications
- Master's degree or higher in a relevant field
- Knowledge of supply chain processes and dynamics is a plus
- Experience in the supply chain domain, particularly in demand and assortment planning
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform
- Experience with containerization technologies such as Docker and Kubernetes
- Knowledge of Big Data technologies such as Spark and Kafka
- Previous experience with Agile methodologies and DevOps practices
- Excellent communication and collaboration skills
- Ability to work effectively in a fast-paced, dynamic environment
- Strong problem-solving skills and attention to detail
- Adaptability and willingness to learn new technologies and methodologies
- Ability to translate complex technical concepts into understandable terms for non-technical stakeholders
- Ability to understand users challenges and associated needs
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