Lead Machine Learning Engineer

Cognizant; New York (NY); Hybrid; USD 130,000 - 155,000; Full time

Benefits offered by this job

Health Insurance

401(k) retirement savings

Paid time off

Career growth and internal mobility

Wellbeing resources

Job summary

Cognizant in New York seeks a Lead Machine Learning Engineer to drive architecture, development, and deployment of Agentic AI systems. You will work with data scientists, engineers, and DevSecOps to deliver scalable, production-ready AI capabilities that create measurable business value.

This hybrid role requires collaboration across teams and strong leadership to mentor engineers, implement MLOps, and advance model governance and observability. A degree and enterprise ML experience are expected.

Qualifications

• Bachelor's degree or equivalent professional experience in CS/engineering or related field.
• Extensive experience designing, developing, deploying, and supporting ML/AI solutions in enterprise environments.
• Strong programming in Python and SQL, with C++ preferred.
• Hands-on experience with ML frameworks like TensorFlow, PyTorch, scikit-learn.
• Strong software engineering fundamentals: system design, RESTful APIs, microservices, version control, testing, distributed systems.
• Experience deploying AI/ML in cloud environments.
• Experience implementing CI/CD pipelines, deployment, model versioning, monitoring.
• Strong data engineering knowledge: ETL, Spark/PySpark, large-scale data ecosystems.
• Excellent communication and collaboration in Agile teams.

Responsibilities

• Lead architecture, design, development, deployment, and optimization of ML models and Agentic AI systems.
• Partner with Data Science, Product, Engineering, and DevSecOps to deliver scalable, secure AI solutions.
• Build and maintain cloud-native AI platforms, data pipelines, and model-serving architectures.
• Implement MLOps and AgentOps with CI/CD/CT, automated testing, monitoring, and governance.
• Mentor engineers, remove blockers, and promote engineering best practices across AI initiatives.

Skills

Python

SQL

C++

TensorFlow

PyTorch

scikit-learn

RESTful APIs

Microservices

MLOps

CI/CD

Data Engineering

Spark/PySpark

GitHub Actions

SageMaker

Jenkins

Education

Bachelor's degree in Computer Science, Engineering, Information Technology, or related field

Tools

TensorFlow

PyTorch

scikit-learn

SageMaker

GitHub Actions

Jenkins

Cloud Platforms

Job description

Lead Machine Learning Engineer (Agentic AI)

About the Role

As a Lead Machine Learning Engineer, you will make an impact by leading the engineering, deployment, and optimization of 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.

This role combines technical leadership, engineering excellence, and innovation. You will help build next-generation AI products and services while fostering a culture of continuous learning, collaboration, and agile delivery.

In This Role, You Will

• Lead the architecture, design, development, deployment, and optimization of machine learning models and Agentic AI systems that solve complex business problems.
• Partner with Data Science, Product, Engineering, and DevSecOps teams to deliver scalable, secure, and production-ready AI solutions.
• Build and maintain cloud-native AI platforms, data ingestion pipelines, memory frameworks, model-serving architectures, and enterprise integrations.
• Implement MLOps and AgentOps best practices, including CI/CD/CT pipelines, automated testing, model monitoring, observability, governance, and performance optimization.
• Mentor engineers, remove technical impediments, evaluate emerging technologies, and promote engineering best practices across AI initiatives.

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.
• Extensive experience designing, developing, deploying, and supporting machine learning and AI solutions in enterprise environments.
• Strong programming expertise in Python and SQL, with experience in C++ preferred.
• Hands-on experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Strong understanding of software engineering fundamentals, including system design, object-oriented programming, RESTful APIs, microservices, version control, testing, and distributed systems.
• Experience developing and deploying AI/ML solutions within cloud environments.
• Experience implementing CI/CD pipelines, automated deployment processes, model versioning, and operational monitoring.
• Strong knowledge of data engineering concepts, including ETL processes, Spark/PySpark, distributed data processing, and large-scale data ecosystems.
• Excellent communication, stakeholder management, problem-solving, and collaboration skills.
• Experience working within Agile delivery environments and coaching team members.

These Will Help You Stand Out

• Experience building and deploying Agentic AI applications and autonomous AI workflows.
• Knowledge of Agent Development Life Cycle (ADLC) methodologies and agent observability platforms.
• Experience utilizing LLM development tools and AI-assisted engineering platforms.
• Hands-on experience with MLFlow, Amazon SageMaker Pipelines, GitHub Actions, Jenkins, CloudBees, or similar MLOps technologies.
• Knowledge of model governance, explainability, drift detection, bias monitoring, and AI risk management practices.
• Experience working with relational, NoSQL, graph databases, semantic data models, and knowledge graph technologies.
• Strong understanding of statistics, probability, linear algebra, multivariate calculus, and predictive analytics.
• Demonstrated ability to mentor and develop engineering talent while fostering innovation and continuous improvement.

We're excited to meet people who share our mission and can make an impact in a variety of ways. 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 $130,000 and $155,000, 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.

Cognizant reserves the right to close this posting earlier based on application volume, business needs, or hiring timelines.