Capgemini
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India · On-site · ₹2 LPA · 2-5 Yrs · Sep 29
Enterprise Software & Network Solutions · 10000+ Employees · Paris, France
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion. Capgemini in India comprises nearly 175,000 team members working across 13 locations: Bangalore, Bhubaneswar, Chennai, Coimbatore, Gandhinagar, Gurugram, Hyderabad, Kolkata, Mumbai, Noida, Pune, Salem and Tiruchirappalli. Get The Future You Want | Learn more about Capgemini in India at www.capgemini.com/in-en.
Hiring: Engineering
What employees say
+ Good company to begin your career as a fresher and retire as an experienced professional
− Not a good org in the middle band, as limited career growth opportunities and pay hike is minimal as compared to market standards
More reviews on the company profile.
Interview experience · Senior Consultant
I attended a walk in interview drive. The arrangement was good and the panel was knowledgeable. The questions were moderately difficult and there was two technical rounds, followed by a HR round.
Average difficulty · India · 17,487 reports
More interview insightsJob description
Overview
Role & responsibilities
Responsibilities
- We are looking for a lead MLOps Engineer lead the design and implementation of scalable, secure, and production-grade ML platforms across Azure platform.
- The role involves architecting end-to-end ML lifecycle solutions, enabling reproducibility, governance, and operational excellence while working closely with data science, platform engineering, and cloud teams.
Qualifications
- Cloud Expertise
- Azure: Azure ML, Azure DevOps, AKS, Functions, Logic Apps, Key Vault
- Databricks: Databricks asset bundles, Unity Catalog, Lakehouse Monitoring, Databricks clusters
- CI/CD for ML and LLMs
- Build and manage ML pipelines using:
- Azure DevOps / Databricks Asset Bundles
- Implement
- Model build, test, validation, and deployment workflows
- Integration with container registries and artifact stores
- Model Lifecycle Management
- End-to-end lifecycle:
- Experiment tracking (MLflow)
- Model versioning, registry, packaging, deployment, rollback
- Exposure to model governance and lineage tracking Databricks Unity Catalog and Lakehouse monitoring
- Infrastructure as Code (IaC)
- Hands-on experience with:
- Terraform (preferred cross-cloud standard)
- Automating infrastructure provisioning for ML workloads
- Containerization & Orchestration
- Strong experience in:
- Docker-based packaging
- Kubernetes platforms: AKS
- Deploying scalable ML inference services
- Automation & Orchestration
- Build automated workflows for:
- Training, validation, deployment, retraining
- Airflow / Azure Container Apps
- ML Observability & Monitoring
- Monitoring tools across cloud ecosystems:
- Azure Monitor, Application Insights
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Job application FAQ
Last updated 3 October 2026
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