14 days ago
Gurgaon, IndiaSenior / Staff+
Responsibilities
- Research and implement MLOps tools, frameworks, and platforms for data science projects.
- Build and manage model deployment, inference, monitoring, retraining, and deployment pipelines.
- Implement drift detection, including data drift and model drift monitoring.
- Support experiment tracking, MLOps architecture, and REST API publishing.
- Raise MLOps maturity through backlog execution and modern automated approaches to data science.
- Conduct internal training and presentations on MLOps tools and their benefits.
Requirements
- 6 to 15 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.
- Experience with cloud platforms, preferably AWS.
Benefits
- Pan India location.
- In-person interview process.
- Immediate to 90-day notice period accepted.
Tech Stack
Categories
About Cognizant
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value. We build full-stack AI solutions powered by deep industry, process and engineering expertise — embedding an organization's unique context into technology systems that amplify human potential and drive tangible outcomes. From strategy to deployment, we help global enterprises move from AI ambition to AI impact and stay ahead in a fast-changing world. See how at cognizant.ai | Follow us @cognizant