Build and improve production-ready Agentic AI and machine learning solutions for real-world business needs.

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

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 C++ exposure preferred.
Experience with ML/DL frameworks including TensorFlow, PyTorch, and scikit-learn.
Knowledge of software engineering principles: object-oriented programming, RESTful APIs, microservices, testing, version control, and system design.
Experience deploying ML solutions in cloud-based environments.
Familiarity with CI/CD pipelines, automated deployment practices, model versioning, and monitoring frameworks.
Understanding of data engineering concepts including ETL, Spark/PySpark, distributed processing, and large-scale data environments.
Strong communication, problem-solving, and collaboration skills.
Experience working in Agile development environments.

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

Hybrid role requiring 3 days per week in a client or Cognizant office in New York, New York.

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.

Anticipated annual salary: $110,000 - $135,000 (depending on experience, qualifications, geographic location, skills, and other job-related factors).
Eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to applicable plan terms.

Applications accepted until September 30, 2026.

Machine Learning Engineer

Job Description