Lead MLOps Engineer; Vertex AI & GCP

"Please note, this role is not able to offer visa transfer or sponsorship now or in the future."

As a Senior MLOps Engineer
, you will make an impact by designing, implementing, and managing the cloud infrastructure, deployment pipelines, and monitoring frameworks that enable machine learning models to run reliably and efficiently in production environments. You will be a valued member of the AI & Data Engineering team and work collaboratively with Data Scientists, Data Engineers, business stakeholders, and global delivery teams to establish and scale MLOps capabilities on Google Cloud Platform (GCP).

• Lead the migration, containerization, and deployment of existing machine learning models into the Google Cloud Vertex AI ecosystem.
• Design, implement, and maintain scalable CI/CD/CT pipelines using Vertex AI Pipelines, Kubeflow, Cloud Build, and related cloud-native technologies.
• Develop and manage model deployment frameworks supporting both real-time and batch inference workloads while ensuring reliability, scalability, and performance.
• Establish monitoring, governance, and lifecycle management processes, including model drift detection, version control, model registry management, and rollback strategies.
• Partner with business stakeholders, Data Science teams, and Data Engineering teams to define requirements, align priorities, and deliver enterprise-grade MLOps solutions.

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 regular onsite presence in Atlanta, Georgia
. 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.

• 7+ years of experience in Data Engineering, Software Engineering, Machine Learning Engineering, or a related technical field.
• 3+ years of hands-on experience building and managing MLOps solutions and deploying machine learning models into production environments.
• Strong expertise with Google Cloud Platform services, including Vertex AI, Big Query, Cloud Storage, Pub/Sub, and related cloud-native technologies.
• Advanced programming experience with Python and SQL, along with hands-on expertise in Docker, Kubernetes, and Google Kubernetes Engine (GKE).
• Proven experience implementing CI/CD pipelines and Infrastructure as Code using tools such as Terraform, Git Hub Actions, Git Lab CI, Jenkins, or Cloud Build.
• Demonstrated ability to lead technical initiatives, collaborate across distributed teams, and communicate effectively with both technical and non-technical stakeholders.

• Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification.
• Experience with machine learning frameworks such as Tensor Flow, PyTorch, or Scikit-Learn.
• Experience implementing model monitoring, governance, and compliance frameworks in enterprise environments.
• Familiarity with Agile and Scrum methodologies.
• Experience mentoring engineers and leading offshore or distributed delivery teams.

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.

Applications will be accepted until September 29th, 2026.

The annual salary for this position is between $130,000 - $155,000 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.

• 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.