Senior MLOps Engineer

Cognizant • United State
Remote
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AI Summary

Design, develop, and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management. Collaborate with data scientists, data engineers, and product teams to operationalize models. Ensure compliance with healthcare data standards, privacy requirements, and governance frameworks.

Key Highlights
MLOps pipeline development
Collaboration with data teams
Healthcare domain expertise
Key Responsibilities
Build, automate, and maintain end-to-end MLOps pipelines
Develop scalable ML workflows
Containerize ML applications
Technical Skills Required
MLOps AWS ML services Databricks ML Docker CI/CD pipelines Git-based workflows DevOps practices
Benefits & Perks
Medical/Dental/Vision/Life Insurance
Paid holidays plus Paid Time Off
401(k) plan and contributions
Nice to Have
Feature stores
Model registries
Real-time inference architectures

Job Description


Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.). Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and we are among the top performing and fastest growing companies in the world.

Candidates must have work authorization that does not require current or future visa sponsorship.

Full time

Remote

Job Description: SR MLOps Engineer

We are seeking an experienced MLOps Engineer to support the development, deployment, and operationalization of machine learning solutions across cloud and lakehouse environments. The ideal candidate will have strong hands‑on experience with MLOps practices, containerization, and modern ML orchestration frameworks. Healthcare domain expertise—particularly in claims systems and coding standards—is a key requirement for this role.

Key Responsibilities

  • Build, automate, and maintain end‑to‑end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
  • Develop scalable ML workflows using AWS, Databricks ML, and related cloud-native services.
  • Containerize ML applications using Docker and manage deployments across environments.
  • Implement model governance, versioning, CI/CD, and automated testing for ML systems.
  • Integrate LangChain / LangGraph components into ML workflows where applicable.
  • Collaborate with data scientists, data engineers, and product teams to operationalize models.
  • Ensure compliance with healthcare data standards, privacy requirements, and governance frameworks.
  • Support LLM and agent-based workflows where applicable

Required Technical Skills

  • Strong experience with MLOps, ML lifecycle automation, and production model deployment.
  • Hands‑on expertise with AWS ML services (SageMaker, Lambda, ECS, ECR) and/or Databricks ML.
  • Proficiency with Docker and container-based deployment patterns.
  • Experience with LangChain or LangGraph (helpful but not required).
  • Strong understanding of CI/CD pipelines, Git-based workflows, and DevOps practices.
  • Familiarity with monitoring and observability tools for ML systems (MLflow, SageMaker Model Monitor, Databricks Model Serving).

Healthcare Domain Expertise

  • Experience working with healthcare claims platforms such as Facets, QNXT, or HealthRules.
  • Understanding of CPT, ICD‑10, HCPCS, and related healthcare coding standards.
  • Knowledge of claims lifecycle, adjudication processes, and payer data models.
  • Ability to translate healthcare business rules into scalable ML and automation solutions.

Preferred Qualifications

  • Experience with feature stores, model registries, and real‑time inference architectures.
  • Exposure to data engineering concepts (Spark, Delta Lake, medallion architecture).
  • Strong analytical, communication, and problem‑solving skills.
  • Ability to work independently and drive technical decisions in a fast‑paced environment.

Application Accepted: 4/15/2026

The annual salary for this position is between $120,000 - $130,000 depending on experience and other qualifications of the successful candidate.

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 the following benefits for this position, subject to applicable eligibility requirements:

  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits 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.

Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.

If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you!

#CB#Ind123


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