MLOps Engineer Job in Hyderabad | Cognizant Careers
Job Description
Summary
Join Cognizant as an MLOps Engineer in Hyderabad and become a key player in deploying, monitoring, and optimizing machine learning models at scale. This role focuses on automating ML workflows using top MLOps tools and cloud platforms like AWS SageMaker, Azure ML Studio, and GCP Vertex AI. Ideal for candidates with expertise in machine learning operations, model deployment pipelines, and Kubernetes orchestration, this full-time hybrid role requires an in-person interview. Advance your career in data science automation with Cognizant, a global leader recognized for innovation and inclusive culture.
Job Details at a Glance
| Job Title | MLOps Engineer / Machine Learning Operations Specialist |
|---|---|
| Location | Hyderabad, India |
| Employment Type | Full-Time |
| Work Model | Hybrid |
| Interview Mode | In-Person |
| Experience Level | Mid to Senior Level |
| Core Skills & Tools | AWS SageMaker, Azure ML Studio, GCP Vertex AI, PySpark, Azure Databricks, MLflow, Kubeflow, Airflow, GitHub Actions, AWS CodePipeline, Kubernetes, AKS, Terraform, FastAPI |
| Date Posted | August 25, 2025 |
Key Responsibilities
- Architect, develop, and maintain end-to-end MLOps pipelines for model deployment, inference, monitoring, and retraining.
- Implement drift detection mechanisms to track data and model performance degradation over time.
- Manage experiment tracking and reproducibility using platforms such as MLflow.
- Research and integrate advanced MLOps frameworks like Kubeflow, AWS SageMaker, Google AI Platform, and Azure ML.
- Deploy and scale machine learning models using Kubernetes clusters and AKS.
- Automate CI/CD pipelines using GitHub Actions, AWS CodePipeline, and related tools to ensure smooth ML model delivery.
- Conduct internal workshops and training to improve MLOps adoption and maturity within the organization.
- Collaborate with data scientists and engineers to streamline model lifecycle management and deployment processes.
Required Skills & Qualifications
- Extensive hands-on experience with Kubernetes and container orchestration in production environments.
- Proven ability to operationalize ML projects using MLOps platforms such as Kubeflow, AWS SageMaker, Azure Machine Learning, or Google AI Platform.
- Strong programming skills in Python for both ML development and automation scripting.
- Familiarity with Bash scripting and Unix/Linux command-line tools.
- Experience designing and implementing robust CI/CD/CT pipelines for ML workflows.
- Knowledge of cloud platforms, with a preference for AWS; familiarity with Terraform and AKS is a plus.
- Solid understanding of ML and AI fundamentals, including hands-on model development experience.
Preferred Experience
- Working knowledge of PySpark and Azure Databricks for big data processing.
- Experience with orchestration tools like Airflow.
- Development experience with FastAPI or similar REST API frameworks.
- Expertise in monitoring data drift and model drift for production ML systems.
- Strong communication skills to lead training and presentations.
Why Choose Cognizant?
- Be part of a global network of 300,000+ professionals fostering innovation and diversity.
- Thrive in an inclusive and supportive work culture that encourages continuous learning.
- Work with cutting-edge AI, ML, and cloud technologies in dynamic, high-impact projects.
- Recognized among Forbes World’s Best Employers 2024.
- Build your career with access to professional development and global opportunities.
Apply Now
Ready to take your career as an MLOps Engineer in Hyderabad to the next level?
Apply now on Cognizant’s official careers page
Please note: In-person interviews are required, and candidates must present valid government-issued ID during the interview process.