Expert
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.
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)
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
Design advanced CI/CD and GitOps workflows for platform and ML assets
Standardize environment promotion (dev → staging → prod) for ML workflows
Define best practices for infrastructure-as-code and platform automation
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
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)
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
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
Hybrid work model: combination of remote and collaborative office experience to enable innovation
Entrepreneurial environment in leading international company
Professional growth possibilities & learning opportunities
Variety of benefits to support your physical, emotional and financial wellbeing
Volunteering opportunities to help external communities
We 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. PepsiCo 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. So, if you’re ready to be a part of a playground for those who think big, we’d love to chat.
*We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability #LI-Hybrid
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