Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role:
- Design, build, and manage end-to-end MLOps pipelines to deploy, monitor, and scale AI/ML models in production environments.
- Collaborate with Data Scientists, AI Engineers, and Software Development teams to operationalize machine learning, NLP, and Generative AI solutions.
- Develop and maintain infrastructure for model training, validation, deployment, monitoring, and automated retraining.
- Implement CI/CD and automation frameworks to accelerate model releases while ensuring reliability and governance.
- Manage containerized and cloud-based deployments using technologies such as Docker, Kubernetes, AWS, Azure, and GCP.
- Drive model performance, scalability,



security, and observability through continuous monitoring, optimization, and troubleshooting.

Your Profile:
- 4+ years of hands-on experience deploying and managing Machine Learning models in production environments.
- Strong expertise in Python and ML/DL frameworks such as TensorFlow, PyTorch, and scikit-learn, along with MLOps platforms like MLflow, Kubeflow, or TFX.
- Experience implementing CI/CD pipelines using tools such as Jenkins, GitLab CI, or similar DevOps technologies.
- Solid understanding of cloud platforms (AWS, Azure, GCP), containerization (Docker), orchestration (Kubernetes), and version control systems (Git).
- Excellent problem-solving, communication, and stakeholder management skills, with the ability to work effectively across cross-functional teams.

What you will love at capgemini:
- Chance to work on cutting-edge AI, Generative AI, Machine Learning, and cloud transfor

📌 Mlops Engineer (Pune)
🏢 Capgemini Sogeti
📍 Pune