Staff Machine Learning Platform Engineer

Faire Wholesale Inc

San Francisco, CA

JOB DETAILS
SALARY
$224,000–$308,000 Per Year
SKILLS
Access Control, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Apache Spark, Artificial Intelligence (AI), Authentication, Best Practices, Big Data, Bridge Building, Cisco Unity, Cloud Computing, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Data Quality, Data Science, Data Sets, Distributed Computing, Docker, Git, GitHub, Identity Data Management, Kotlin, Machine Learning, MySQL, Performance Modeling, Performance Tuning/Optimization, Python Programming/Scripting Language, Retail, SQL (Structured Query Language), Statistics, Technical Writing, Training/Teaching
LOCATION
San Francisco, CA
POSTED
30+ days ago

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:

  • Category
  • Technologies
  • 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

San Francisco: the pay range for this role is $224,000 to $308,000 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.

About the Company

F

Faire Wholesale Inc