Staff Machine Learning Platform Engineer (Kitchener)
Staff Machine Learning Platform Engineer (Kitchener)
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Kitchener, Canada
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Posted: yesterday
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Description
About Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we’re using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.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. You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.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 modelsImplement 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 (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 setsEstablish 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 Robust hands‑on expertise with Databricks, Spark, Delta Lake, and MLflow Proficiency in Python, SQL, and distributed systems conceptsExperience 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 Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get thejob doneTech 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 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 benefits. 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.Hybrid Work Arrangement
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in‑office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.Why you’ll love working at Faire
Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.Real rewards: Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Equity, Opportunity, Accommodation, and Privacy
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.
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Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we’re using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.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. You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.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 modelsImplement 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 (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 setsEstablish 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 Robust hands‑on expertise with Databricks, Spark, Delta Lake, and MLflow Proficiency in Python, SQL, and distributed systems conceptsExperience 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 Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get thejob doneTech 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 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 benefits. 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.Hybrid Work Arrangement
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in‑office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.Why you’ll love working at Faire
Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.Real rewards: Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Equity, Opportunity, Accommodation, and Privacy
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.
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Highlights
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Company nameFaire
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Job positionStaff Machine Learning Platform Engineer (Kitchener)
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