MLops Engineer
Capgemini Pune
Applications close on July 25, 2026
- Corporate Common and Invest
- Software Engineering
Job Description
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
- Opportunity to work on cutting-edge AI, Generative AI, Machine Learning, and cloud transformation programs for global clients.
- Collaborative and inclusive work environment that encourages innovation, learning, and knowledge sharing.
- Access to industry-leading technologies, cloud platforms, and modern MLOps ecosystems.
- Continuous learning opportunities through certifications, technical academies, and career development programs.
- Exposure to large-scale enterprise AI implementations, enabling you to make a real business impact.
- Flexible and people-centric culture focused on growth, well-being, and long-term career progression.