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MLOps (Machine Learning Operations) and Model accuracy Engineer
Capgemini Sogeti —Gandhinagar, Coimbatore, Tamil Nadu
- Remote
- Azure
- DevOps
- System design
- Flexible schedule

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MLOps (Machine Learning Operations) and Model accuracy Engineer
Capgemini Sogeti —Gandhinagar, Coimbatore, Tamil Nadu
Enforce strong engineering practices including modular design, automated testing, code quality, and scalability standards.

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MLOps (Machine Learning Operations) and Model accuracy Engineer

Capgemini Sogeti -
Gandhinagar, Coimbatore, Tamil Nadu

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Job details

Permanent

Benefits

Flexible schedule

Qualifications

CI/CD
Cloud infrastructure
Azure
Go
Kubernetes
DevOps
System design
Java
AWS
Docker
Machine learning
Continuous integration
Python

Full job description

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 and build scalable, reliable backend and platform systems optimized for ML workloads, ensuring high availability and performance
Enforce strong engineering practices including modular design, automated testing, code quality, and scalability standards
Develop and manage cloud-native infrastructure with Kubernetes, containers, and microservices, while optimizing for cost and resilience
Establish and scale CI/CD pipelines across both application and ML lifecycles, with full observability (logging, metrics, tracing)
Architect and implement end-to-end MLOps pipelines, from data ingestion through deployment, monitoring, and automated retraining
Drive automation in model lifecycle management including versioning, experiment tracking, reproducibility, and governance using tools like MLflow, Kubeflow, and Airflow
Define, monitor, and continuously improve model performance using key metrics (accuracy, latency, drift, bias), with robust evaluation and A/B testing frameworks
Lead cross-functional teams and collaborate with stakeholders to deliver scalable AI solutions while shaping the ML platform strategy and adoption roadmap

Your Skills

Strong foundation in Software Engineering (Java/Python/Go) and system design
Expertise in DevOps practices (CI/CD, Docker, Kubernetes, Infrastructure as Code)
Proven experience in MLOps frameworks and model lifecycle management
Deep understanding of model accuracy, evaluation metrics, and monitoring strategies
Hands-on experience with cloud platforms (GCP/AWS/Azure)
Prior experience managing engineering teams

Why you will love working at Capgemini

At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities.
We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain a healthy work life balance.

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

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MLOps (Machine Learning Operations) and Model accuracy Engineer

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