Lead ML Ops/DevOps Engineer – AI Engineering

FICO

Lead ML Ops/DevOps Engineer on FICO’s Generative AI team building scalable infrastructure. Develop, deploy, and manage ML pipelines and systems for practical applications in AI.

Posted 7/13/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $140,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data and ML pipelines using AWS services and infrastructure as code tools. Proficient in operationalizing machine learning models and ensuring high availability and security of cloud infrastructure.

Highest-signal resume keywords

AWS Services ProficiencyInfrastructure As Code (IaC) ExpertiseCI/CD Pipeline DevelopmentKubernetes Management (EKS)Observability Tools Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DataOpsMLOpsMachine Learning OperationalizationWorkflow AutomationTerraformCloudFormationHelmPython ScriptingGitOps PracticesData Governance

Soft Skills

CollaborationCommunication

Tools & Technologies

GitHub ActionsArgoCDPrometheusGrafanaDatadogOpenTelemetry

Industry Keywords

Cloud SecurityKubernetesCost EfficiencyComplianceIdentity & Access Management

Tech Stack

Tools & technologies

AWSCloudEC2GrafanaJenkinsKubernetesPrometheusPythonTerraform

About the role

Key responsibilities & impact

Design, build, and maintain scalable, resilient data and ML pipelines, infrastructure, and workflows using tools such as Terraform, GitHub Actions, ArgoCD, Helm, and others.
Automate infrastructure provisioning and configuration management using cloud-native services (preferably AWS) with tools like Terraform, CloudFormation.
Design, containerize, and manage Kubernetes (EKS) clusters and/or ECS environments in AWS.
Collaborate with development teams to optimize performance, deployment, and cost.
Partner with DevOps and SRE teams to ensure high availability, observability, scalability, and security of the data and ML infrastructure.
Work closely with Data Scientists and ML Engineers to operationalize machine learning models, including building CI/CD pipelines for model training, validation, and deployment.
Implement observability for data pipelines and ML services using tools like Prometheus, Grafana, Datadog, or similar.
Develop and maintain automated pipelines for model retraining, monitoring drift, and versioning in production.
Support experimentation and prototyping in areas such as Machine Learning and Generative AI, transitioning successful prototypes into production systems.
Ensure cloud infrastructure is secure, compliant, and cost-efficient, following best practices in governance, identity, and access management.

Requirements

What you’ll need

8+ years of experience in DataOps, MLOps, or related fields, with 3+ years focused on ML model operationalization and workflow automation.
Proficient in AWS services including EC2, S3, IAM, ACM, Route 53, CloudWatch, EKS, and ECS.
Experience with infrastructure as code (IaC) tools such as Terraform, CloudFormation, and Helm.
Familiarity with CI/CD for ML pipelines, GitOps practices, and tools like GitHub Actions, Jenkins, or Argo Workflows.
Strong scripting and automation skills using Python, or GitHub workflows.
Solid understanding of observability and monitoring tools (e.g., Prometheus, Grafana, Datadog, or OpenTelemetry).
Solid understanding of security best practices for cloud and Kubernetes environments, including secrets management, identity & access control, and policy enforcement.
Strong understanding with data governance, lineage, and metadata management is a plus.
Excellent collaboration and communication skills, with a proven ability to work effectively in cross-functional, globally distributed teams.
A bachelor’s degree in computer sciences, or a related discipline, or equivalent hands-on industry experience.

Benefits

Comp & perks

An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others.
The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences.
Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.
An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.