MLOps Engineer
hace 2 días
Cornellà de Llobregat
ph3Overview /h3 pWe are seeking a Mid-Level MLOps Engineer to build, operate, and evolve our Kubeflow‑based ML platform on Azure. This role focuses on enabling reliable, scalable, and cost‑efficient ML workflows by designing CI/CD pipelines, managing Kubernetes‑based ML infrastructure, improving platform observability, and supporting MLE and Data Science teams across the model lifecycle. /p pThe ideal candidate is hands‑on, comfortable working across infrastructure and ML workflows, and motivated to operationalize best practices in MLOps. /p h3Responsibilities /h3 h3Platform Infrastructure /h3 ul liDeploy, configure, and operate Kubeflow components on Azure Kubernetes Service (AKS) /li liSupport Kubernetes workloads for training, inference, and batch pipelines /li liManage container images, registries, and ML runtime environments /li liAssist with Kubeflow and Kubernetes upgrades under senior guidance /li /ul h3CI/CD Automation /h3 ul liBuild and maintain CI/CD pipelines for ML workflows and platform services /li liAutomate model training, validation, and deployment pipelines /li liImplement reproducibility and versioning for data, models, and pipelines /li /ul h3Observability Reliability /h3 ul liImplement logging, monitoring, and alerting at the platform level /li liDiagnose and resolve workflow, pipeline, and infrastructure failures /li liSupport SLAs and reliability objectives for ML platforms /li /ul h3Collaboration Enablement /h3 ul liWork closely with MLEs and Data Scientists to onboard workflows onto Kubeflow /li liProvide best practices, templates, and documentation for ML teams /li liCollaborate with Infra and Security teams on access control and compliance needs /li /ul h3Cost Awareness Optimization /h3 ul liAssist with collecting and reporting costs at Kubeflow namespace or workflow level /li liIdentify optimization opportunities related to compute usage and scheduling /li /ul h3Qualifications /h3 ul li3–6 years of experience in MLOps, DevOps, or Platform Engineering /li liHands‑on experience with Kubeflow, Kubernetes, Terraform (IaC), and containerized ML workloads /li liStrong experience with Azure cloud services (AKS, ACR, Storage, Networking, IAM, AD Groups) /li liProficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch, scikit‑learn) /li liExperience building CI/CD pipelines (GitHub Actions, Azure DevOps, Argo, etc.) /li liUnderstanding of ML lifecycle management (training, inference, monitoring, retraining) /li liFamiliarity with observability tools (Prometheus, Grafana, Azure Monitor, DataDog) /li liStrong collaboration and communication skills /li /ul h3Benefits /h3 ul liHybrid work model: combination of remote and collaborative office experience to enable innovation /li liEntrepreneurial environment in leading international company /li liProfessional growth possibilities learning opportunities /li liVariety of benefits to support your physical, emotional and financial wellbeing /li liVolunteering opportunities to help external communities /li /ul h3About PepsiCo /h3 pWe believe that culture should be at the cornerstone of everything we do at PepsiCo. We are agile, innovative and not afraid of failure. We want our team to come to work every day excited to explore new ways to bring enjoyment, refreshment and fun to the world. /p pPepsiCo Positive (pep+) is the future of our organization – a strategic end‑to‑end transformation, with sustainability at the center of how we will create growth and value by operating within planetary boundaries and inspiring positive change for the planet and people. /p pSo, if you’re ready to be a part of a playground for those who think big, we’d love to chat. /p p*We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability. /p /p #J-18808-Ljbffr