Senior MLOps / AIOps Platform Engineer MLflow, GCP, Vertex AI, IBM Watsonx, Terraform

Job description

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Job Summary

We are seeking a Senior MLOps / AIOps Platform Engineer with deep DevSecOps expertise and hands-on experience managing enterprise-grade AI/ML platforms.

This critical role focuses on building, configuring, and operationalizing secure, scalable, and reusable infrastructure and pipelines that support AI and ML initiatives across the enterprise.

The ideal candidate will have a strong background in Infrastructure as Code (IaC), pipeline automation, and platform engineering, with specific experience configuring and maintaining IBM watsonx and Google Cloud Vertex AI environments.

**Key Responsibilities**

Platform Engineering & Operations

+ Lead the provisioning, configuration, and ongoing support of **IBM watsonx** and **Google Cloud Vertex AI** platforms.
+ Ensure platforms are **production-ready, secure, cost-efficient, and performant** across training, inference, and orchestration workflows.
+ Manage lifecycle tasks such as patching, upgrades, integrations, and service reliability.
+ Partner with security, compliance, and product teams to align platforms with enterprise and regulatory standards.

Enterprise MLOps / AIOps Enablement

+ Define and implement **standardized MLOps/AIOps practices** across business units for consistency and scalability.
+ Build and maintain **reusable workflows** for model development, deployment, retraining, and monitoring.
+ Provide **onboarding, enablement, and support** to AI/ML teams adopting enterprise platforms and tools.
+ Support **development/deployment of GenAI** applications and maintain them at an Enterprise scale.

DevSecOps Integration

+ Embed **security and compliance guardrails** across the ML lifecycle, including CI/CD pipelines and IaC templates.
+ Implement **policy-as-code, access controls, vulnerability scanning, and automated compliance checks** .
+ Ensure all deployments meet **enterprise and regulatory requirements** (HIPAA, SOX, FedRAMP, etc.).

Infrastructure as Code & Automation

+ Design and maintain **IaC templates** (Terraform, Pulumi, Ansible, CloudFormation) for reproducible ML infrastructure.
+ Build and optimize **CI/CD pipelines** for AI/ML assets including data pipelines, training workflows, deployment artifacts, and monitoring systems.
+ Enforce best practices around **automation, reusability, and observability** of infrastructure and workflows.

Monitoring, Logging & Observability

+ Implement **comprehensive observability** for AI/ML workloads using Prometheus, Grafana, Stackdriver, or Datadog.
+ Monitor both **infrastructure health** (CPU, memory, cost) and **ML-specific metrics** (model drift, data integrity, anomaly detection).
+ Define KPIs and usage metrics to measure **platform performance, adoption, and operational health** .

**Qualifications**

Education

+ Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

Experience

+ 5+ years in **MLOps, DevOps, Platform Engineering, or Infrastructure Engineering** .
+ 2+ years applying **DevSecOps practices** (secure CI/CD, vulnerability management, policy enforcement).
+ Hands-on experience configuring and managing **enterprise AI/ML platforms (IBM watsonx, Google Vertex AI)** .
+ Demonstrated success in building and scaling **ML infrastructure, automation pipelines, and platform support models** .

Technical Skills

+ Proficiency with **IaC tools** (Terraform, Pulumi, Ansible, CloudFormation).
+ Strong scripting skills in **Python and Bash** .
+ Deep understanding of **containerization and orchestration** (Docker, Kubernetes).
+ Experience with **model lifecycle tools** (MLflow, TFX, Vertex Pipelines, or equivalents).
+ Familiarity with **secrets management, policy-as-code, access control** , and monitoring tools.
+ Working knowledge of **data engineering concepts** and their integration into ML pipelines.

Preferred

+ **Cloud certifications** (e.g., GCP Professional ML Engineer, AWS DevOps Engineer, IBM Cloud AI Engineer).
+ Experience supporting platforms in **regulated industries** (HIPAA, FedRAMP, SOX, PCI-DSS).
+ Contributions to **open-source projects** in MLOps, automation, or DevSecOps.
+ Familiarity with **responsible AI practices** including governance, fairness, interpretability, and explainability.
+ Hands-on experience with **enterprise feature stores, model monitoring frameworks, and fairness toolkits** .

**Type de contrat:**

en CDI

_Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés._

Required Skill Profession

Other General