[Job- 21621] Senior MLOps Engineer Senior, Brazil

We are tech transformation specialists, uniting human expertise with AI to create scalable tech solutions.With over 6,500 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality.
Hello there!
The 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 & PlatformsPipeline OrchestrationKedro, Argo Workflows, ArgoCDExperiment TrackingMLflowContainerization & DeploymentDocker, Kubernetes (EKS), AWS ECR, Helm ChartsMonitoring & ObservabilityGrafana, Prometheus, AWS CloudWatchInfrastructure & DevOpsAWS, Terraform (preferred), JFrog ArtifactoryCollaborative EnvironmentsJupyterHub, Git, GitHub Actions / GitLab CIData VersioningDVC, Delta Lake (preferred)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 & BackgroundDegree in Computer Engineering, Data Science, Information Systems, or related fields.Proven experience deploying and maintaining ML solutions in production environments.
#LI-AM2Our benefits:
-Health and dental insurance-Meal and food allowance-Childcare assistance-Extended paternity leave-Wellhub (Gympass)-TotalPass-Profit-sharing (PLR)-Life insurance-CI&T University-Discount club-Free online platform dedicated to physical, mental, and overall well-being-Pregnancy and responsible parenting course-Partnerships with online learning platforms-Language learning platformAnd many more!More details about our benefits here: https://ciandt.com/br/pt-br/carreiras


Collaboration 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.