at Capgemini
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**Senior Machine Learning Engineer (MLOps) - Empowering Global Organizations** Drive strategic projects to success as our Senior MLOps Engineer, leveraging your Software Engineering and DevOps expertise. Embedded in key projects, you'll enhance code quality, automate CI/CD pipelines, and develop reusable ML frameworks. Key responsibilities include building, maintaining, and documenting ML packages, collaborating with cross-functional teams, creating feature stores, and implementing performance monitoring. Required: Bachelor's degree in a relevant field, 5+ years in Data Analytics, 3+ years in ML Ops/Engineering, strong Python proficiency, and experience creating python packages. Join Capgemini, a global AI-powered partner, transforming businesses through technology and collaboration.
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Full Job Description
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
MLOps Engineer
Your Role:
We are looking for a highly capable Senior MLOps Engineer with a strong Software Engineering and DevOps background. As a Senior MLOps Engineer, you will be embedded and supporting a revenue generation or cost optimization project, ensuring its success in production by improving the code, creating automated CI/CD testing, and developing frameworks that can be reused for other similar projects.
- Build, maintain, and document machine learning frameworks (python packages) used across multiple projects.
- Support a project team with Data Scientists, Business Stakeholders, Analysts, and Data Engineers.
- Develop reusable feature stores for rules-based and AI/ML models.
- Implement monitoring capabilities for model performance and effectiveness in production.
- Automate CI/CD testing and deployments incorporating MLOps best practices.
Your Profile:
- • Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
- 5+ years of overall experience in Data Analytics.
- 3+ years of experience with ML Engineering and/or ML Ops. Up to 2 years of Software Engineering or Data Engineering experience can also count towards this requirement. Sharp critical thinking skills and ability to learn and question complex processes and solutions.
- Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
- Experience creating python packages.
- Well-developed software engineering skills, including use of proper development, QA, and production environments, object-oriented programming, version control, and knowledge of multiple programming languages.
- Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
- Proficiency in SQL
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Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com
