Staff Machine Learning Platform Engineer

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Logo of Faire

Faire

1001 - 5000 employees

Founded 2017

đŸ€ B2B

đŸ›ïž eCommerce

🛒 Retail

B2B ‱ eCommerce ‱ Retail

Faire is a wholesale marketplace that connects independent retailers with unique products from global brands. It offers a platform for retailers to discover and purchase products that resonate with their customers, featuring various categories including women-owned, eco-friendly, and handmade items. With benefits like easy returns on first orders and flexible payment options, Faire aims to simplify the purchasing experience for retailers while supporting diverse and local brands.

📋 Description

‱ Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows ‱ Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows ‱ Teach data scientists to use the ML platform and advance models from notebook to production ‱ Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage ‱ Build CI/CD pipelines for ML using Terraform and Git-based workflows such as GitHub Actions ‱ Optimize performance, reliability, and cost across training and inference workloads ‱ Configure IAM and RBAC for sensitive datasets ‱ Establish observability for data quality, model performance, and platform health ‱ Build and maintain ML Platform technical documentation

🎯 Requirements

‱ 8+ years of experience building production ML or data platforms ‱ A degree in Computer Science, Engineering, Statistics, or a related technical field; graduate level is preferred ‱ Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow ‱ Proficiency in Python, SQL, and distributed systems concepts ‱ Experience with cloud platforms and infrastructure-as-code ‱ Understanding of MLOps best practices, including CI/CD, monitoring, reproducibility, and security ‱ Experience supporting multiple ML teams in a shared platform environment ‱ Ability to take ownership of orphaned problems and acquire missing knowledge to complete the work ‱ Proficiency with relevant technologies including Kotlin, PyTorch, Kafka, Snowflake, Airflow, AWS, Kubernetes, Docker, and Terraform

đŸ–ïž Benefits

‱ Equity ‱ Comprehensive benefits ‱ Competitive pay ‱ Latest enterprise AI tools ‱ Flexible remote work option for candidates located in Ontario, Canada

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