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 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
- Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done
Tech Stack
Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following:
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