Capgemini

MLOps Engineer

Posted On

Jan. 23, 2026

Location

Bangalore, Karnataka

Experience Level

Experienced Professionals

Job Type

Permanent

Apply By

Feb. 25, 2026

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 robust ML pipelines and services for training; validation; and model deployment

Collaborate with data scientists to transition models from experimentation to production.

Build reusable infrastructure components using best practices in DevOps and MLOps.

Implement model serving infrastructure with high availability and low latency (REST/gRPC).

Automate testing; versioning; and monitoring of ML models using CI/CD workflows.

Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutionsorapplications.1. Applies scientific methods to analyse and solve software engineering problems.2. Heorshe is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. Hisorher work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of hisorher software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.

Your profile

Design and build robust ML pipelines and services for training; validation; and model deployment.

Collaborate with data scientists to transition models from experimentation to production.

Build reusable infrastructure components using best practices in DevOps and MLOps.

Implement model serving infrastructure with high availability and low latency (REST/gRPC).

Automate testing; versioning; and monitoring of ML models using CI/CD workflows.

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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