2 days ago
Coimbatore, IndiaSenior / Staff+
Responsibilities
- Research and implement MLOps tools, frameworks, and platforms for Data Science projects.
- Develop model deployment, inference, monitoring, retraining, and drift-detection pipelines.
- Design MLOps architecture and support experiment tracking and REST API publishing.
- Improve organizational MLOps maturity through an activity backlog and automated Data Science practices.
- Conduct internal training and presentations on MLOps tools and their benefits.
Requirements
- 5+ to 12 years of experience.
- Wide experience with Kubernetes.
- Experience operationalizing Data Science projects using at least one MLOps framework or platform such as Kubeflow, AWS SageMaker, Google AI Platform, Azure Machine Learning, DataRobot, or DKube.
- Good understanding of machine learning and AI concepts, with hands-on ML model development experience.
- Proficiency in Python for machine learning and automation tasks.
- Good knowledge of Bash and Unix command-line tools.
- Experience implementing CI/CD/CT pipelines.
- Cloud platform experience, preferably AWS, is advantageous.
Tech Stack
Apache AirflowAWSAzureBashDatabricksFastAPIGitHub ActionsGoogle Cloud PlatformKubernetesMLflowPythonTerraform
Categories
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.