Staff Machine Learning Platform Engineer

🕒 August 14

🇨🇦 Canada – Remote

💵 $216k - $297k / year

⏰ Full Time

🔴 Lead

🏗️ Platform Engineer

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Faire

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

🤝 B2B

🛍️ 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

🏖️ Benefits

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