Note: The job is a remote job and is open to candidates in USA. FICO is seeking a Lead MLOps/DevOps Engineer to join their Generative AI team, focusing on innovative solutions for their platform. The role involves designing and maintaining scalable data and ML pipelines, deploying production systems, and collaborating with teams to enhance AI capabilities.
Responsibilities
- Design, build, and maintain scalable, resilient data and ML pipelines, infrastructure, and workflows using tools such as Terraform, GitHub Actions, ArgoCD, Helm, and other
- 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
Skills
- 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
- Excellent collaboration and communication skills, with a proven ability to work effectively in cross-functional, globally distributed teams
- Bachelor's degree in computer sciences, or a related discipline, or equivalent hands-on industry experience
- Strong understanding with data governance, lineage, and metadata management is a plus
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