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Staff Machine Learning Platform Engineer

1 month, 1 week ago
United States
Full-time
Lead
Machine Learning Engineer
DevOps and Infrastructure
Apache Airflow Apache Spark AWS CI/CD CockroachDB Databricks Datadog Docker GitHub Actions Kafka Kotlin Kubernetes Machine Learning MLflow MLOps MySQL Python PyTorch SageMaker Snowflake SQL Terraform
Apply Now
Faire

Faire

Faire is an online wholesale marketplace connecting independent retailers with unique merchandise from around the world. With flexible payment terms, free returns, and personalized recommendations, Faire empowers small businesses to compete with larger...

Textiles, Apparel & Luxury Goods
1K-5K
Founded 2017
$1500M raised
View All Jobs 9

Description

  • 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 move models from notebooks into production on the ML platform.
  • Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage.
  • Build CI/CD pipelines for machine learning using Terraform and Git-based workflows such as GitHub Actions.
  • Optimize performance, reliability, and cost across training and inference workloads.
  • Configure IAM and RBAC for sensitive datasets.
  • Establish observability for data quality, model performance, and platform health.
  • Build and maintain technical documentation for the ML platform.

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, including CI/CD, monitoring, reproducibility, and security.
  • Experience supporting multiple ML teams in a shared platform environment.
  • Experience with Kotlin, PyTorch, Kafka, Snowflake, Fivetran, Iceberg, Datadog, Airflow, Cockroach DB, or MySQL is preferred.
  • Experience with AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, or Terraform is preferred.
  • Familiarity with generative AI tools such as Claude Sonnet 4.5 and ChatGPT 5.2 is listed in the tech stack.

Benefits

  • Salary range of $224,000 to $308,000 per year in San Francisco.
  • Eligibility for equity.
  • Hybrid work schedule with 3 days per week in the office.
  • Flexibility to work remotely up to 4 weeks per year in hybrid roles.
  • Reasonable accommodation support during the recruitment process.
  • Equal employment opportunity commitment.
  • Access to benefits, though specific plan details are not listed.

Interested in this position?

Apply directly on the company website

Apply Now

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