Lead ML Ops/DevOps Engineer – AI Engineering

🕒 Julho 13

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FICO

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1956

💼 Consultoria

🛡️ Seguros

🏥 Saúde

Consulting • Insurance • Healthcare

FICO é uma empresa líder em analytics e software, reconhecida pelo FICO® Score, uma ferramenta amplamente utilizada por credores para avaliar o risco de crédito. A empresa oferece uma plataforma abrangente que aproveita dados, IA e machine learning para impulsionar a tomada de decisões inteligentes e o engajamento de clientes em diversos setores. As soluções da FICO abrangem detecção de fraudes, credit scoring e gestão do ciclo de vida do cliente, tornando-a vital para segmentos como serviços financeiros e telecomunicações. Seus produtos inovadores ajudam as empresas a otimizar resultados por meio de analytics em tempo real, composabilidade de negócios e gestão de cenários.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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.