Machine Learning Engineer

Cognizant; New York (NY); Hybrid; USD 110,000 - 135,000; Full time

Benefits offered by this job

Medical insurance

HSA/FSA benefits

Life insurance

401(k) retirement plan

Paid time off

Employee Assistance Program (EAP)

Wellbeing resources

Professional development and training

Career growth and internal mobility

Recognition programs

Job summary

Cognizant is seeking a Machine Learning Engineer (Agentic AI) in New York for designing, developing, deploying, and optimizing Agentic AI systems. You will work with Data Scientists, Data Engineers, DevSecOps, Product teams, and business stakeholders to deliver scalable, production-ready AI capabilities that create measurable business value.

The role focuses on building next-generation AI products with modern engineering practices and a hybrid work model requiring 3 days per week in New York

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field or equivalent professional experience.
• Experience designing, developing, deploying, and supporting machine learning applications in enterprise environments.
• Strong programming in Python and SQL, with exposure to C++ preferred.
• Experience with TensorFlow, PyTorch, and scikit-learn.
• Knowledge of RESTful APIs, microservices, testing, version control, and system design.
• Experience deploying ML solutions within cloud-based environments.
• Familiarity with CI/CD pipelines, automated deployment practices, model versioning, and monitoring frameworks.
• Knowledge of ETL processes, Spark/PySpark, distributed processing, and large-scale data environments.
• Strong communication, problem-solving, and collaboration skills; Agile experience.

Responsibilities

• Design, develop, deploy, and optimize machine learning models and Agentic AI systems that address real-world business challenges.
• Collaborate with Data Science, Product, Engineering, and DevSecOps teams to develop scalable, secure, and production-ready AI solutions.
• Build and maintain cloud-native AI applications, data ingestion pipelines, memory frameworks, and model-serving architectures.
• Implement MLOps and AgentOps best practices, including automated testing, CI/CD/CT pipelines, monitoring, observability, and model governance.
• Contribute to continuous improvement initiatives by evaluating emerging technologies and applying engineering best practices across AI development projects.

Skills

Python

SQL

C++

TensorFlow

PyTorch

scikit-learn

MLOps

CI/CD

Model deployment

Cloud platforms

Agentic AI

Education

Bachelor's degree in Computer Science or related field

Tools

MLFlow

SageMaker Pipelines

GitHub Actions

Jenkins

CloudBees

PySpark

Kubernetes

Job description

Machine Learning Engineer (Agentic AI)

About the Role

As a Machine Learning Engineer, you will make an impact by designing, developing, deploying, and optimizing Agentic AI systems and machine learning solutions that solve complex business challenges. You will be a valued member of the AI and Data Engineering team and work collaboratively with Data Scientists, Data Engineers, Data Analysts, DevSecOps professionals, Product teams, and business stakeholders to deliver scalable, production-ready AI capabilities that create measurable business value.

In this role, you will help build next-generation AI products and services while leveraging modern engineering practices to deliver innovative customer experiences.

In This Role, You Will

• Design, develop, deploy, and optimize machine learning models and Agentic AI systems that address real-world business challenges.
• Collaborate with Data Science, Product, Engineering, and DevSecOps teams to develop scalable, secure, and production-ready AI solutions.
• Build and maintain cloud-native AI applications, data ingestion pipelines, memory frameworks, and model-serving architectures.
• Implement MLOps and AgentOps best practices, including automated testing, CI/CD/CT pipelines, monitoring, observability, and model governance.
• Contribute to continuous improvement initiatives by evaluating emerging technologies and applying engineering best practices across AI development projects.

Work Model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3 days per week in a client or Cognizant office in New York, New York. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What You Need to Have to Be Considered

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent professional experience.
• Experience designing, developing, deploying, and supporting machine learning applications in enterprise environments.
• Strong programming skills in Python and SQL, with exposure to C++ preferred.
• Experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Knowledge of software engineering principles, including object-oriented programming, RESTful APIs, microservices, testing, version control, and system design.
• Experience developing and deploying ML solutions within cloud-based environments.
• Familiarity with CI/CD pipelines, automated deployment practices, model versioning, and monitoring frameworks.
• Knowledge of data engineering concepts, including ETL processes, Spark/PySpark, distributed processing, and large-scale data environments.
• Strong communication, problem-solving, and collaboration skills.
• Experience working in Agile development environments.

These Will Help You Stand Out

• Experience developing Agentic AI applications and autonomous AI workflows.
• Familiarity with Agent Development Life Cycle (ADLC) methodologies and observability frameworks.
• Experience using LLM development tools and AI-assisted software engineering platforms.
• Knowledge of MLFlow, Amazon SageMaker Pipelines, GitHub Actions, Jenkins, CloudBees, or similar MLOps technologies.
• Understanding of model governance, explainability, drift detection, bias monitoring, and AI risk management practices.
• Experience working with relational, NoSQL, and graph databases.
• Knowledge of statistics, probability, linear algebra, predictive analytics, and machine learning optimization techniques.
• Passion for continuous learning and staying current with emerging AI technologies.

We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Salary and Other Compensation

The annual salary for this position is anticipated to be between $110,000 and $135,000, depending on experience, qualifications, geographic location, skills, and other job-related factors.

This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.

Benefits

Cognizant offers a comprehensive and competitive benefits package designed to support the health, wellbeing, and financial security of our associates and their families, including:

• Medical, dental, and vision insurance
• Health Savings Account (HSA) and Flexible Spending Accounts (FSA), where applicable
• Company-paid life insurance and disability coverage
• 401(k) retirement savings plan with company contributions, subject to plan provisions
• Paid time off, company holidays, and leave programs
• Employee Assistance Program (EAP)
• Wellbeing and mental health resources
• Professional development, training, and certification opportunities
• Career growth and internal mobility programs
• Associate recognition and reward programs

Benefits may vary by location and employment status and are subject to change.

Application Deadline

Applications will be accepted until September 30, 2026.