Responsibilities
- Build and deploy scalable machine learning models.
- Develop and maintain end-to-end machine learning pipelines.
- Collaborate with data scientists and engineers to integrate ML solutions into production systems.
- Analyze and preprocess data to support model development.
- Optimize models for performance, scalability, and efficiency.
Requirements
- Proven experience in machine learning engineering, including deployment and monitoring.
- Proficiency in Python and core data science skills such as clustering, classification, and regression. A plus is a knowledge of working with images and texts.
- Experience with cloud platforms and containerization tools (e.g., AWS, Docker).
- Understanding of software engineering practices (version control, testing, CI/CD).
- Background in mathematical programming, operational research, or optimization techniques.
- Experience with combinatorial optimization, linear programming, or mixed-integer programming.
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