Machine Learning Engineer
hace 2 semanas
At Capgemini, we empower our engineers to shape their careers and collaborate with a global community of innovators. Our mission is to help leading organizations unlock the value of technology and build a more sustainable, inclusive world.
Key Responsibilities
- Collaborate with business stakeholders and data science teams to define data engineering and MLOps requirements.
- Transform business and data science prototypes into scalable machine learning solutions.
- Solve complex problems with multi-layered data sets and optimize existing machine learning libraries and frameworks.
- Develop reusable data and feature stores for rules-based and AI/ML models.
- Design and implement alerting tool frameworks for monitoring productionized model performance and effectiveness.
- Automate deployments incorporating MLOps best practices into productionalized solutions.
- Document frameworks and machine-learning processes.
- Develop simple front-end reporting solutions for stakeholders to consume insights.
Required Skills
- Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
- Well-developed software engineering fundamentals, including use of proper development, QA, and production environments.
- Experience creating Python packages.
- Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
- Proficiency in Databricks & MLFlow.
- Proficiency in SQL.
About Capgemini
As a global leader in engineering services, we bring together a team of engineers, scientists, and architects to help innovative companies unleash their potential. From autonomous vehicles to lifesaving robots, our digital and software technology experts think outside the box to provide unique R&D and engineering services across all industries.
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