2 days ago
Marcon, Italy +4 moreSenior
Responsibilities
- Develop AI, deep learning, and Generative AI solutions, including RAG architectures.
- Create ETL and data-processing pipelines.
- Integrate vector databases and expose services through APIs.
- Implement CI/CD processes and MLOps practices.
- Deploy, log, and monitor models in production.
- Collaborate with multidisciplinary teams using Agile methodologies.
Requirements
- Experience developing and putting scalable, maintainable AI and Generative AI solutions into production across their full lifecycle.
- Experience with hyperscalers such as Azure, AWS, or GCP and data platforms such as Databricks or Snowflake.
- Knowledge of Python and PySpark.
- Strong MLOps, DevOps, and CI/CD skills.
- Knowledge of Git and version-control practices.
- Experience with ETL pipelines, RAG architectures, vector databases, APIs, logging, monitoring, and release platforms.
- Good English-language proficiency.
- Azure DevOps, MLflow, Docker, and Kubernetes experience is preferred.
Benefits
- Flexible working options, including remote work and flexible hours, to support work-life balance.
- Professional growth and career-development opportunities.
- Inclusive workplace supporting diversity and social responsibility.
- Permanent employment under the Italian Metalworking Industry collective agreement, with hybrid work in Milan, Turin, Bologna, Marcon, or Rome.
Tech Stack
Categories
Data EngineeringML Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.