MLOps Engineer - Hyderabad

Cognizant is seeking a skilled and proactive MLOps Engineer to join our AI/ML team in Hyderabad, Telangana, India. This is an exciting opportunity for experienced professionals (6-12 years) to play a key role in designing, implementing, and maintaining robust MLOps pipelines and infrastructure across cloud platforms. You will collaborate closely with data scientists, software engineers, and DevOps teams to operationalize machine learning models, ensuring scalable, secure, and automated deployment and monitoring.

Job Summary:

As an MLOps Engineer, you will be instrumental in the end-to-end lifecycle of machine learning models. This includes designing and implementing model deployment, monitoring, and retraining pipelines. You will build and maintain CI/CD/CT pipelines for ML workflows, leveraging tools such as MLFlow, Kubeflow, Airflow, GitHub Actions, and AWS CodePipeline. Developing and managing inference, monitoring, and drift detection pipelines (data drift, model drift) is crucial. You will architect scalable and secure MLOps infrastructure using Kubernetes, AKS, and Terraform, and publish/manage REST APIs for model inference using FastAPI. Tracking experiments and model performance metrics, collaborating with cross-functional teams to elevate MLOps maturity, and conducting internal training sessions are also key aspects of this role.

Key Responsibilities:

• Design and implement model deployment, monitoring, and retraining pipelines.
• Build and maintain CI/CD/CT pipelines for ML workflows using tools like MLFlow, Kubeflow, Airflow, GitHub Actions, and AWS CodePipeline.
• Develop and manage inference, monitoring, and drift detection pipelines (data drift, model drift).
• Architect scalable and secure MLOps infrastructure using Kubernetes, AKS, and Terraform.
• Publish and manage REST APIs for model inference using FastAPI.
• Track experiments and model performance metrics.
• Collaborate with cross-functional teams to raise MLOps maturity across the organization.
• Conduct internal training and presentations on MLOps tools and best practices.

Required Skills & Technologies:

• Cloud Platforms: AWS SageMaker, Azure ML Studio, GCP Vertex AI
• Big Data & Processing: PySpark, Azure Databricks
• MLOps Tools: MLFlow, Kubeflow, Airflow, GitHub Actions, AWS CodePipeline
• Infrastructure & Automation: Kubernetes, AKS, Terraform, FastAPI
• Programming Languages: Python (ML and automation), Bash, Unix CLI

Qualifications:

• Bachelor's or Master’s degree in Computer Science, Data Science, or related field.
• Proven experience in operationalizing ML models using MLOps frameworks.
• Strong understanding of ML/AI concepts and hands-on experience in model development.
• Experience with cloud-native development and container orchestration.
• Familiarity with agile methodologies and DevOps practices.

Preferred Qualifications:

• Certification in AWS, Azure, or GCP.
• Experience with DataRobot, DKube, or similar platforms.
• Exposure to enterprise-level ML systems and governance.

Interview Date: 6th September 2025 in Hyderabad

Mode of Interview: In-Person (Scheduled)

Note: This is a scheduled interview process. Candidates will be invited based on shortlisting and prior appointment. This is not a walk-in interview.