About Faire

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we use technology, data, and machine learning to connect this thriving community of entrepreneurs worldwide.

We’re looking for smart, resourceful, and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.

What You Will Do 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 our 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 Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets Establish observability for data quality, model performance, and platform health Build and maintain ML Platform technical documentation What it takes 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 environment Active ownership of orphaned problems and willingness to assimilate missing knowledge to get the job done Tech Stack

Languages: Python, SQL, Kotlin.

ML Frameworks: PyTorch, MLflow. Big Data & Processing: Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, CockroachDB, MySQL. Cloud & Infrastructure: AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform.

Generative AI: Claude Sonnet 4.5, ChatGPT 5.2.

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. This role will also be eligible for equity and advantages. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Equal Employment Opportunity

Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. Faire is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process.

To request reasonable accommodation, please fill out our Accommodation Request Form ( Privacy For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (

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