MLOps Engineer Job in Bangalore | Cognizant Careers
Job Description
Summary
Are you an experienced MLOps Engineer looking for a challenging role in Bangalore? Join Cognizant’s innovative technology team and drive the deployment, monitoring, and management of machine learning models using leading MLOps tools and cloud platforms like AWS SageMaker, Azure ML Studio, and GCP Vertex AI. This full-time, hybrid position requires in-person interviews and offers exciting opportunities to advance your career in machine learning operations, model deployment, and AI automation. Become a key player in building scalable, automated MLOps pipelines that deliver real business impact.
Job Details at a Glance
| Job Title | MLOps Engineer / Machine Learning Operations Specialist |
|---|---|
| Location | Bangalore, India |
| Employment Type | Full-Time |
| Work Model | Hybrid |
| Interview Mode | In-Person |
| Experience Level | Mid to Senior Level |
| Key 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
- Design, build, and maintain automated MLOps pipelines for model deployment, inference, monitoring, and retraining.
- Implement drift detection strategies including data drift and model drift monitoring to maintain model performance.
- Track and manage experiments using tools like MLflow for reproducibility and governance.
- Research and integrate MLOps frameworks and platforms such as Kubeflow, AWS SageMaker, Google AI Platform, and Azure Machine Learning.
- Publish REST APIs for machine learning models and manage scalable containerized deployments using Kubernetes and AKS.
- Develop CI/CD pipelines with GitHub Actions, AWS CodePipeline, and other automation tools for continuous integration and delivery of ML models.
- Lead knowledge sharing sessions to elevate MLOps maturity across teams and projects.
- Collaborate cross-functionally to adopt agile, modern, and automated Data Science practices.
Required Skills & Qualifications
- Strong hands-on experience with Kubernetes and container orchestration in production environments.
- Proven expertise in operationalizing ML models using MLOps platforms such as Kubeflow, AWS SageMaker, Azure Machine Learning, or Google AI Platform.
- Solid programming skills in Python, with proficiency in Bash scripting and Unix command-line tools.
- Experience designing and implementing CI/CD/CT pipelines for ML and software deployments.
- Knowledge of cloud platforms with preference for AWS, familiarity with Terraform, and AKS.
- Good understanding of machine learning and AI concepts along with practical ML model development experience.
- Ability to automate and optimize ML workflows for scalable and reliable production systems.
Preferred Experience
- Working knowledge of big data technologies such as PySpark and Azure Databricks.
- Experience with workflow orchestration tools like Airflow.
- Familiarity with REST API development frameworks like FastAPI.
- Exposure to data drift and model drift detection techniques.
- Contributions to open-source MLOps projects or active participation in AI/ML communities.
- Strong communication skills for conducting training sessions and cross-team collaboration.
Why Work at Cognizant?
- Join a global leader with a diverse community of over 300,000 associates worldwide.
- Thrive in an inclusive, collaborative, and innovative work environment.
- Gain exposure to cutting-edge AI, ML, and cloud projects with top-tier clients.
- Benefit from comprehensive learning, growth opportunities, and a supportive culture.
- Recognized as one of Forbes World’s Best Employers 2024.
Apply Now
Ready to accelerate your career as an MLOps Engineer in Bangalore?
Apply now on the official Cognizant Careers portal
Note: This position requires in-person interviews and valid government-issued ID during the recruitment process.