Capgemini - MLOps Engineer

Your Role :

- Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment

- Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools

- Develop and maintain CI/CD pipelines for ML workflows

- Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)

- Optimize ML infrastructure for performance, scalability, and cost-efficiency

Your Profile :

- Strong programming skills in Python (5+ years), with experience in ML frameworks; understanding of ML-specific testing and validation techniques

- Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques

- Proficiency in cloud platform (AWS) and their ML-specific services with atleast 2-3 years of experience.

- Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)

- Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques

What youll love about working here :

- We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance

- Our focus will be your career growth & professional development to support you in exploring the world of opportunities.

- Equip yourself with valuable certifications & training programmes in the latest technologies such as MLOps, Machine Learning