Senior Staff Machine Learning Platform Engineer

🔥 0 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Faire

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

🤝 B2B

🛍️ eCommerce

🛒 Retail

B2B • eCommerce • Retail

Faire is a wholesale marketplace that connects independent retailers with unique products from global brands. It offers a platform for retailers to discover and purchase products that resonate with their customers, featuring various categories including women-owned, eco-friendly, and handmade items. With benefits like easy returns on first orders and flexible payment options, Faire aims to simplify the purchasing experience for retailers while supporting diverse and local brands.

📋 Description

• Define and drive the long-term architecture of Faire’s ML platform, including training, inference, feature management, and governance • Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability • Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns • Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow • Optimize performance, reliability, and cost of the ML platform • Evaluate and integrate emerging Databricks features • Stay current with developments in machine learning and AI • Serve as senior ML technical advisor to data science and production engineering teams • Represent Faire at ML conferences and meetups • Mentor ML engineers and raise the overall machine learning engineering standard at Faire

🎯 Requirements

• 10–12 years of experience building and improving large-scale ML or data platforms • A degree in Computer Science, Engineering, Statistics, or a related technical field is required by the wording, with graduate level preferred • Deep expertise in Databricks lakehouse architecture, including Unity Catalog governance, Workflows orchestration, and cost optimization • Proven ability to design systems supporting multiple data science teams and production workloads • Strong background in distributed systems, ML infrastructure, and cloud architecture • Demonstrated technical leadership across teams and organizations; ability to influence without authority • Proficiency with Python, SQL, Kotlin, PyTorch, PySpark, MLflow, Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, CockroachDB, MySQL, AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform, Claude Sonnet 4.5, and ChatGPT 5.2 • Experience integrating LLM workflows into enterprise platforms is a plus • Open-source ML infrastructure contributions or research publications are a very strong plus

🏖️ Benefits

• Equity • Comprehensive benefits • Competitive pay • Latest enterprise AI tools • Equal access to opportunities, growth, and success • Reasonable accommodation throughout the recruitment process