Requirements

8+ years of experience building production ML or data platforms A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field 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 Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security Experience supporting multiple ML teams in a shared platform workplace Active ownership of orphaned problems and a willingness to assimilate missing knowledge to get the job done What the job involves

Design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance Serve as the technical bridge between data science and production engineering Join a small, critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape 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 how to utilize the ML platform to advance development from notebook to production for our most critical models 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 (e.g., GitHub Actions) Optimize performance, reliability, and cost across training and inference workloads Configure IAM and RBAC for sensitive data sets Establish observability for data quality, model performance, and platform health Build and maintain ML Platform technical documentation Tech Stack

Languages: Python, SQL, Kotlin ML Frameworks: PyTorch, MLFlow Big Data & Processing: Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL Cloud & Infrastructure: AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform Generative AI: Claude Sonnet 4.5, ChatGPT 5.2

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📌 Staff Machine Learning Platform Engineer (Winnipeg)
🏢 Faire
📍 Winnipeg