Senior ML Platform Engineer

URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly)

full-time

Posted on: 9/23/2025

Origin: • 🇺🇸 United States • Pennsylvania

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Senior

AirflowAWSAzureCloudDockerKafkaKubernetesPythonSparkTerraform

About the role

Design, implement, and maintain Nuuly’s ML platform to support feature stores, training pipelines, inference services, and retraining workflows
Develop automated pipelines and infrastructure for model deployment, configuration management, and reproducibility across environments
Architect cloud-native solutions for distributed training, high-throughput batch scoring, and low-latency real-time inference
Build systems to monitor model health, detect drift, track infrastructure performance, and integrate with alerting/incident response
Manage containerized workloads (Docker, Kubernetes) and provision cloud infrastructure with Terraform, Helm, and related IaC tools
Partner with data scientists, ML engineers, and data engineers to translate model requirements into scalable, reliable platform capabilities
Evaluate and integrate emerging technologies in MLOps, cloud, and data infrastructure to advance platform efficiency and scalability

4–6 years of relevant experience in ML platform engineering, MLOps, or cloud infrastructure for ML systems
Strong proficiency in Python and software engineering best practices
Deep expertise in Kubernetes, containerization, and cloud-native architectures
Proven experience with CI/CD, orchestration, and ML lifecycle tools (e.g., Argo, Airflow, Kubeflow, MLflow)
Hands-on experience with cloud platforms (Google Cloud, AWS, or Azure) and infrastructure-as-code (Terraform, Helm)
Strong knowledge of observability practices: monitoring, logging, metrics, and alerting for ML/production systems
Familiarity with distributed computing and streaming platforms (Kafka, Spark, Flink)
Bonus: Experience implementing security, compliance, and cost-optimization strategies in ML platforms