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Cognizant logo

MLOPS Engineer

Cognizant

MLOPS Engineer

Cognizant logo

Cognizant

full-time

Posted: December 7, 2025

Number of Vacancies: 1

Job Description

Role : MLOps Engineer
Location - AIA Bangalore

Experience- 3 to 12years

Key words -Skillset

  • AWS SageMaker, Azure ML Studio, GCP Vertex AI
  • PySpark, Azure Databricks
  • MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline
  • Kubernetes, AKS, Terraform, Fast API

Responsibilities

  • Model Deployment, Model Monitoring, Model Retraining
  • Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline
  • Drift Detection, Data Drift, Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

Job Responsibilities:

· Research and implement MLOps tools, frameworks and platforms for our Data Science projects.

· Work on a backlog of activities to raise MLOps maturity in the organization.

· Proactively introduce a modern, agile and automated approach to Data Science.

· Conduct internal training and presentations about MLOps tools’ benefits and usage.

Required experience and qualifications:

· Wide experience with Kubernetes.

· Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube).

· Good understanding of ML and AI concepts. Hands-on experience in ML model development.

· Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.

· Experience in CI/CD/CT pipelines implementation.

· Experience with cloud platforms - preferably AWS - would be an advantage.

The Cognizant community:
We are a high caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.

  • Cognizant is a global community with more than 300,000 associates around the world.
  • We don’t just dream of a better way – we make it happen.
  • We take care of our people, clients, company, communities and climate by doing what’s right.
  • We foster an innovative environment where you can build the career path that’s right for you.

About us:
Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World’s Best Employers 2025) is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com

Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com with your request and contact information.

Disclaimer:
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

About the Role/Company

  • Cognizant is a global community with more than 300,000 associates around the world
  • We don’t just dream of a better way – we make it happen
  • We take care of our people, clients, company, communities and climate by doing what’s right
  • We foster an innovative environment where you can build the career path that’s right for you
  • Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era
  • Headquartered in the U.S., Cognizant is a member of the NASDAQ-100 and one of Forbes World’s Best Employers 2025
  • Cognizant is consistently listed among the most admired companies in the world
  • Cognizant helps clients lead with digital at www.cognizant.com
  • Cognizant is an equal opportunity employer
  • Applicants may be required to attend interviews in person or by video conference
  • Candidates may be required to present their current state or government issued ID during each interview

Key Responsibilities

  • Research and implement MLOps tools, frameworks and platforms for Data Science projects
  • Work on a backlog of activities to raise MLOps maturity in the organization
  • Proactively introduce a modern, agile and automated approach to Data Science
  • Conduct internal training and presentations about MLOps tools’ benefits and usage
  • Model Deployment
  • Model Monitoring
  • Model Retraining
  • Deployment pipeline
  • Inference pipeline
  • Monitoring pipeline
  • Retraining pipeline
  • Drift Detection
  • Data Drift
  • Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

Required Qualifications

  • Wide experience with Kubernetes
  • Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube)
  • Good understanding of ML and AI concepts
  • Hands-on experience in ML model development
  • Proficiency in Python used both for ML and automation tasks
  • Good knowledge of Bash and Unix command line toolkit
  • Experience in CI/CD/CT pipelines implementation

Preferred Qualifications

  • Experience with cloud platforms - preferably AWS

Skills Required

  • AWS SageMaker
  • Azure ML Studio
  • GCP Vertex AI
  • PySpark
  • Azure Databricks
  • MLFlow
  • KubeFlow
  • AirFlow
  • Github Actions
  • AWS CodePipeline
  • Kubernetes
  • AKS
  • Terraform
  • Fast API

Additional Requirements

  • Experience: 3 to 12 years
  • Location: AIA Bangalore

Locations

  • India

Salary

Salary not disclosed

Estimated Salary Rangemedium confidence

800,000 - 1,500,000 INR / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • AWS SageMakerintermediate
  • Azure ML Studiointermediate
  • GCP Vertex AIintermediate
  • PySparkintermediate
  • Azure Databricksintermediate
  • MLFlowintermediate
  • KubeFlowintermediate
  • AirFlowintermediate
  • Github Actionsintermediate
  • AWS CodePipelineintermediate
  • Kubernetesintermediate
  • AKSintermediate
  • Terraformintermediate
  • Fast APIintermediate

Required Qualifications

  • Wide experience with Kubernetes (experience)
  • Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube) (experience)
  • Good understanding of ML and AI concepts (experience)
  • Hands-on experience in ML model development (experience)
  • Proficiency in Python used both for ML and automation tasks (experience)
  • Good knowledge of Bash and Unix command line toolkit (experience)
  • Experience in CI/CD/CT pipelines implementation (experience)

Preferred Qualifications

  • Experience with cloud platforms - preferably AWS (experience)

Responsibilities

  • Research and implement MLOps tools, frameworks and platforms for Data Science projects
  • Work on a backlog of activities to raise MLOps maturity in the organization
  • Proactively introduce a modern, agile and automated approach to Data Science
  • Conduct internal training and presentations about MLOps tools’ benefits and usage
  • Model Deployment
  • Model Monitoring
  • Model Retraining
  • Deployment pipeline
  • Inference pipeline
  • Monitoring pipeline
  • Retraining pipeline
  • Drift Detection
  • Data Drift
  • Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

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Tags & Categories

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Cognizant logo

MLOPS Engineer

Cognizant

MLOPS Engineer

Cognizant logo

Cognizant

full-time

Posted: December 7, 2025

Number of Vacancies: 1

Job Description

Role : MLOps Engineer
Location - AIA Bangalore

Experience- 3 to 12years

Key words -Skillset

  • AWS SageMaker, Azure ML Studio, GCP Vertex AI
  • PySpark, Azure Databricks
  • MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline
  • Kubernetes, AKS, Terraform, Fast API

Responsibilities

  • Model Deployment, Model Monitoring, Model Retraining
  • Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline
  • Drift Detection, Data Drift, Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

Job Responsibilities:

· Research and implement MLOps tools, frameworks and platforms for our Data Science projects.

· Work on a backlog of activities to raise MLOps maturity in the organization.

· Proactively introduce a modern, agile and automated approach to Data Science.

· Conduct internal training and presentations about MLOps tools’ benefits and usage.

Required experience and qualifications:

· Wide experience with Kubernetes.

· Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube).

· Good understanding of ML and AI concepts. Hands-on experience in ML model development.

· Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.

· Experience in CI/CD/CT pipelines implementation.

· Experience with cloud platforms - preferably AWS - would be an advantage.

The Cognizant community:
We are a high caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.

  • Cognizant is a global community with more than 300,000 associates around the world.
  • We don’t just dream of a better way – we make it happen.
  • We take care of our people, clients, company, communities and climate by doing what’s right.
  • We foster an innovative environment where you can build the career path that’s right for you.

About us:
Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World’s Best Employers 2025) is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com

Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com with your request and contact information.

Disclaimer:
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

About the Role/Company

  • Cognizant is a global community with more than 300,000 associates around the world
  • We don’t just dream of a better way – we make it happen
  • We take care of our people, clients, company, communities and climate by doing what’s right
  • We foster an innovative environment where you can build the career path that’s right for you
  • Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era
  • Headquartered in the U.S., Cognizant is a member of the NASDAQ-100 and one of Forbes World’s Best Employers 2025
  • Cognizant is consistently listed among the most admired companies in the world
  • Cognizant helps clients lead with digital at www.cognizant.com
  • Cognizant is an equal opportunity employer
  • Applicants may be required to attend interviews in person or by video conference
  • Candidates may be required to present their current state or government issued ID during each interview

Key Responsibilities

  • Research and implement MLOps tools, frameworks and platforms for Data Science projects
  • Work on a backlog of activities to raise MLOps maturity in the organization
  • Proactively introduce a modern, agile and automated approach to Data Science
  • Conduct internal training and presentations about MLOps tools’ benefits and usage
  • Model Deployment
  • Model Monitoring
  • Model Retraining
  • Deployment pipeline
  • Inference pipeline
  • Monitoring pipeline
  • Retraining pipeline
  • Drift Detection
  • Data Drift
  • Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

Required Qualifications

  • Wide experience with Kubernetes
  • Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube)
  • Good understanding of ML and AI concepts
  • Hands-on experience in ML model development
  • Proficiency in Python used both for ML and automation tasks
  • Good knowledge of Bash and Unix command line toolkit
  • Experience in CI/CD/CT pipelines implementation

Preferred Qualifications

  • Experience with cloud platforms - preferably AWS

Skills Required

  • AWS SageMaker
  • Azure ML Studio
  • GCP Vertex AI
  • PySpark
  • Azure Databricks
  • MLFlow
  • KubeFlow
  • AirFlow
  • Github Actions
  • AWS CodePipeline
  • Kubernetes
  • AKS
  • Terraform
  • Fast API

Additional Requirements

  • Experience: 3 to 12 years
  • Location: AIA Bangalore

Locations

  • India

Salary

Salary not disclosed

Estimated Salary Rangemedium confidence

800,000 - 1,500,000 INR / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • AWS SageMakerintermediate
  • Azure ML Studiointermediate
  • GCP Vertex AIintermediate
  • PySparkintermediate
  • Azure Databricksintermediate
  • MLFlowintermediate
  • KubeFlowintermediate
  • AirFlowintermediate
  • Github Actionsintermediate
  • AWS CodePipelineintermediate
  • Kubernetesintermediate
  • AKSintermediate
  • Terraformintermediate
  • Fast APIintermediate

Required Qualifications

  • Wide experience with Kubernetes (experience)
  • Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube) (experience)
  • Good understanding of ML and AI concepts (experience)
  • Hands-on experience in ML model development (experience)
  • Proficiency in Python used both for ML and automation tasks (experience)
  • Good knowledge of Bash and Unix command line toolkit (experience)
  • Experience in CI/CD/CT pipelines implementation (experience)

Preferred Qualifications

  • Experience with cloud platforms - preferably AWS (experience)

Responsibilities

  • Research and implement MLOps tools, frameworks and platforms for Data Science projects
  • Work on a backlog of activities to raise MLOps maturity in the organization
  • Proactively introduce a modern, agile and automated approach to Data Science
  • Conduct internal training and presentations about MLOps tools’ benefits and usage
  • Model Deployment
  • Model Monitoring
  • Model Retraining
  • Deployment pipeline
  • Inference pipeline
  • Monitoring pipeline
  • Retraining pipeline
  • Drift Detection
  • Data Drift
  • Model Drift
  • Experiment Tracking
  • MLOps Architecture
  • REST API publishing

Target Your Resume for "MLOPS Engineer" , Cognizant

Get personalized recommendations to optimize your resume specifically for MLOPS Engineer. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "MLOPS Engineer" , Cognizant

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

TechnologyIT ServicesTechnologyConsulting

Related Jobs You May Like

No related jobs found at the moment.