at Capgemini
ConsultanciesPosted 5 days ago
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**ML Ops and Model Accuracy Engineer** Design and build scalable ML platforms. Streamline ML lifecycles using tools like MLflow, Kubeflow, and Airflow. Optimize model performance with CI/CD pipelines, ensuring high availability and quality. Collaborate cross-functionally to deliver AI solutions and shape ML strategy. Requirements: Expertise in Software Engineering (Java/Python/Go), DevOps practices, MLOps, cloud platforms (GCP/AWS/Azure), and proven team management experience.
- Compensation
- Not specified
- City
- Not specified
- Country
- India
Currency: Not specified
Full Job Description
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds 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
