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# MLOps Architect

- **Company:** PepsiCo
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** Computing Platforms, Microsoft Azure, Cloud Computing, Continuous Integration, DevOps, Octopus Deploy, Azure Machine Learning, Software Engineering, Autoscaling, Reliability of Systems, Usage Tracking, Git Flow, Kubernetes, Machine Learning Operations, Terraform
- **Published:** August 23, 2026
- **Apply:** https://www.jobleads.com/es/job/e29bb8b4326cfdd5a7940e3b31f43cc68

## About the Role

* 7+ years of experience in MLOps, Platform Engineering, DevOps, or ML Infrastructure
 * Deep expertise in Kubeflow internals, Kubernetes architecture, and multi-tenant ML platforms
 * Strong architectural experience on Azure (AKS, Networking, Security, Governance, Cost Management)
 * Proven experience leading platform upgrades (Kubeflow & Kubernetes) with minimal disruption
 * Advanced CI/CD, GitOps, and Infrastructure-as-Code experience (Terraform, Helm, Argo CD)
 * Experience designing platform-level observability, governance, and FinOps frameworks
 * Strong leadership, technical decision-making, and stakeholder management skills

## Description

We are looking for a MLOps Architect to own the end-to-end design, evolution, and governance of our Kubeflow-based MLOps platform on Azure. This role is responsible for platform architecture, long-term technical strategy, system reliability, upgrades, cost optimization, and introducing new MLOps capabilities while ensuring zero or minimal impact to running workflows.

The role partners closely with ML Engineers, Data Science leaders, Cloud Infrastructure, Software Engineering, and Business stakeholders to translate ML requirements into scalable, secure, and cost-effective platform solutions., Platform Architecture & Strategy

 * Define and own the end-to-end architecture of the Kubeflow-based MLOps platform
 * Establish platform standards for scalability, security, reliability, and multi-tenancy
 * Drive the roadmap for new MLOps capabilities (feature stores, registries, serving, governance)

Kubernetes & Kubeflow Lifecycle Management

 * Plan and execute Kubeflow and Kubernetes version upgrades with minimal workflow disruption
 * Evaluate and introduce new Kubeflow components and ecosystem tools
 * Ensure backward compatibility and migration strategies for existing workflows, * Architect platform-wide observability (metrics, logs, traces, ML-specific monitoring)
 * Implement governance controls for access, data usage, and environment isolation
 * Ensure compliance with enterprise security standards and cloud governance policies

FinOps & Cost Attribution

 * Design and operate cost attribution models per workflow, team, or business unit
 * Partner with Finance and Business teams to provide cost visibility and optimization insights
 * Drive cost optimization strategies (autoscaling, spot instances, right-sizing)

Cross-Functional Leadership

 * Act as technical advisor to Data Science, MLE, Infrastructure, and Software teams
 * Collaborate with Business stakeholders to align platform capabilities with business goals
 * Mentor junior MLOps engineers and set engineering best practices


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