Lead ML Ops/DevOps Engineer - AI Engineering

1 Fair Isaac Corporation; United States; On-site; USD 140,000 - 220,000; Full time

Benefits offered by this job

Competitive compensation

Inclusive culture

Work-life balance

Pay range: $140,000–$220,000

Job summary

FICO is seeking a Lead MLOps/DevOps Engineer on the Generative AI team to deploy and scale production ML systems across fraud detection, decision automation, and workflow orchestration. You will design data and ML pipelines, implement CI/CD, manage EKS/ECS on AWS, and collaborate with Data Scientists to operationalize models while ensuring security, observability, and cost efficiency.

This role offers highly competitive compensation and a culture that values ownership and collaboration, with

Qualifications

• 8+ years in DataOps or MLOps, with 3+ years ML model ops & workflow automation.
• Proficiency with AWS services (EC2, S3, IAM, ACM, Route53, CloudWatch, EKS, ECS).
• Experience with IaC tools: Terraform, CloudFormation, Helm.
• CI/CD for ML pipelines; GitOps with GitHub Actions, Jenkins, or Argo Workflows.
• Strong scripting/automation in Python or GitHub workflows.
• Observability tooling: Prometheus, Grafana, Datadog, OpenTelemetry.
• Security best practices for cloud/Kubernetes: secrets, IAM, policy enforcement.
• Knowledge of data governance, lineage, metadata management is a plus.

Responsibilities

• Design, build, and maintain scalable ML pipelines, infrastructure, and workflows.
• Automate infrastructure provisioning with AWS and IaC tools.
• Manage Kubernetes (EKS) clusters and ECS environments in AWS.
• Collaborate with development teams to optimize performance, deployment, and cost.
• Partner with DevOps/SRE to ensure high availability, observability, security.
• Operationalize ML models with CI/CD for training, validation, deployment.
• Implement observability for data pipelines and ML services.

Skills

MLOps

DataOps

CI/CD

GitOps

Python scripting

AWS

Terraform

CloudFormation

Kubernetes (EKS)

ECS

Observability

Security best practices

Data governance

Education

Bachelor's degree in CS or related

Tools

AWS

Terraform

CloudFormation

Helm

GitHub Actions

ArgoCD

Jenkins

Argo Workflows

Kubernetes (EKS)

ECS

Prometheus

Grafana

Datadog

OpenTelemetry

Job description

Overview

As a Lead MLOps/DevOps Engineer on our Generative AI team, you’ll be at the cutting edge of language model applications. You will build innovative solutions across key areas of the FICO platform, including fraud detection, decision automation, workflow orchestration, system optimization, and internal productivity.

You will deploy production systems, troubleshoot operational issues, and integrate services at scale.

Bring next‑generation AI capabilities in production and collaborate with a world‑class team to build robust, scalable infrastructure and accelerate innovation across FICO’s platform.

Responsibilities

• 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 and 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 data and ML infrastructure.
• Work closely with Data Scientists and ML Engineers to operationalize machine learning models, building CI/CD pipelines for model training, validation, and deployment.
• Implement observability for data pipelines and ML services using tools such as 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 governance, identity, and access‑management best practices.

Qualifications

• 8+ years of experience in DataOps, MLOps, or related fields, with 3+ years focused on ML model operationalization and workflow automation.
• Proficiency with AWS services including EC2, S3, IAM, ACM, Route53, CloudWatch, EKS, and ECS.
• Experience with infrastructure‑as‑code 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 (Prometheus, Grafana, Datadog, or OpenTelemetry).
• Strong knowledge of security best practices for cloud and Kubernetes environments, including secrets management, identity & access control, and policy enforcement.
• Strong understanding of 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, a related discipline, or equivalent industry experience.

Benefits

• Highly competitive compensation, benefits and rewards programs that encourage professional growth.
• Inclusive culture reflecting core values: Act Like an Owner, Delight Our Customers, and Earn the Respect of Others.
• Work/life balance with employee resource groups, social events, and a people‑first work environment.
• Targeted base pay range of $140,000 to $220,000, adjusted for candidate knowledge, skills, and experience.

Equal Employment Opportunity

FICO promotes a culture of inclusion and seeks to attract a diverse set of candidates for each job opportunity. We are an equal employment opportunity employer and are proud to offer employment and advancement opportunities to all candidates without regard to race, color, ancestry, religion, sex, national origin, pregnancy, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Research has shown that women and candidates from underrepresented communities may not apply for an opportunity if they do not meet all stated qualifications. While our qualifications are clearly related to role success, each candidate’s profile is unique and strengths in certain skill and/or experience areas can be equally effective. If you believe you have many, but not necessarily all, of the stated qualifications, we encourage you to apply. Information submitted with your application is subject to the FICO privacy policy at https://www.fico.com/en/privacy-policy