Nuuly Senior ML Platform Engineer

Nuuly is seeking a Senior ML Platform Engineer who will focus on building and evolving the machine learning platform that powers end-to-end ML operations. You will design, automate, and maintain the infrastructure, tooling, and observability systems that enable rapid experimentation, seamless deployment, and reliable operation of ML services at scale. Your work will empower data scientists and ML engineers to deliver high-impact ML solutions efficiently and with confidence.

• Platform Engineering: Design, implement, and maintain Nuuly’s ML platform to support feature stores, training pipelines, inference services, and retraining workflows.
  
• Automation & CI/CD: Develop automated pipelines and infrastructure for model deployment, configuration management, and reproducibility across environments.
  
• Scalability & Reliability: Architect cloud-native solutions for distributed training, high-throughput batch scoring, and low-latency real-time inference.
  
• Monitoring & Observability: Build systems to monitor model health, detect drift, track infrastructure performance, and integrate with alerting/incident response.
  
• Cloud & Infrastructure Management: Manage containerized workloads (Docker, Kubernetes) and provision cloud infrastructure with Terraform, Helm, and related IaC tools.
  
• Collaboration: Partner with data scientists, ML engineers, and data engineers to translate model requirements into scalable, reliable platform capabilities
  
• Continuous Improvement: 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.

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URBN celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, sex (including gender, pregnancy, sexual orientation, and gender identity or expression), religion, creed, age, physical or mental disability, national origin or ancestry, ethnicity, citizenship, service in the uniformed services, genetic information, or any other protected characteristic as established by law. We believe strongly in fostering a safe, fair and respectful work environment. To ensure compliance with our non-discrimination and anti-harassment policies, we offer anti-harassment training to managers and employees.