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Senior Mlops Engineer Senior, Brazil - São Paulo / SP

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Detalhes da Vaga

  • Escolaridade Não Informado
  • Segmento Não Informado
  • Salário Não Informado
  • Área de AtuaçãoDiversos / Outros

O que você irá fazer

  • With over 6,500 CI&Ters around the world, weve built partnerships with more than 1,000 clients during our 30 years of history.
  • Artificial Intelligence is our reality.
  • Hello there!The MLOps Engineer RoleThe MLOps Engineer is responsible for designing, implementing, and maintaining scalable, reproducible, and auditable machine learning pipelines.
  • This role bridges the gap between data science, engineering, and operations by enabling reliable deployment, monitoring, and governance of machine learning models in production environments.
  • Responsibilities:Develop and maintain end-to-end ML pipelines using Kedro, following best practices in modularity, version control, and data lineage.
  • Manage experiment tracking and model versioning with MLflow (Tracking, Projects, Model Registry).
  • Deploy models using ArgoCD for GitOps workflows and Kubernetes (EKS) for container orchestration and scalability.
  • Set up and manage observability and performance monitoring using the Grafana + Prometheus stack.
  • Handle artifact and dependency management using JFrog Artifactory.
  • Operate and administer collaborative computing environments with JupyterHub for multi-user scenarios.
  • Automate the full ML lifecycle using CI/CD pipelines integrated with AWS (EKS, ECR, S3, Lambda, CloudWatch).
  • Requirements:Tools & Platforms:MLflowContainerization & DeploymentMonitoring & ObservabilityInfrastructure & DevOpsCollaborative Environments (JupyterHub, Git, GitHub Actions / GitLab CI)Strong understanding of version control for code, data, and models.
  • Knowledge of security, authentication, and governance in data platforms.
  • Practical experience with automated deployment of ML models in real-time and batch settings.
  • Familiarity with ML-specific CI/CD, including testing and model drift validation.
  • Excellent communication skills and ability to interface between data and engineering teams.
  • Education & Background:Degree in Computer Engineering, Data Science, Information Systems, or related fields.
  • Proven experience deploying and maintaining ML solutions in production environments.
  • #LI-AM2Benefits:Health and dental insuranceMeal and food allowanceExtended paternity leaveWellhub (Gympass)TotalPassLife insuranceCI&T UniversityDiscount clubFree online platform dedicated to physical, mental, and overall well-beingPregnancy and responsible parenting coursePartnerships with online learning platformsCollaboration is our superpower, diversity unites us, and excellence is our standard.
  • We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment.
  • We encourage applications from diverse and underrepresented groups to our job positions.
  • #J-18808-Ljbffr

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