Senior Staff Machine Learning Platform Engineer

This is a fully remote position, open to applicants in Arizona, +30 more states.

📋 Description

• Take charge of the technical vision and advancement of Faire’s ML platform.

• Define and lead the long-term architecture for training, inference, feature management, and governance.

• Set company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability.

• Spearhead the adoption and advanced utilization of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns.

• Design scalable ML workflows using Spark, Delta Lake, and MLflow.

• Enhance the performance, reliability, and cost-effectiveness of the ML platform.

• Assess and incorporate new features from Databricks.

• Stay engaged with the latest innovations in machine learning and AI.

• Serve as a senior ML technical advisor to Faire’s data science and production engineering teams.

• Represent Faire at ML conferences and networking events.

• Mentor ML engineers to elevate the overall machine learning standards at Faire.

⛳️ Requirements

• 10–12 years of experience in building and enhancing large-scale ML or data platforms.

• A degree in Computer Science, Engineering, Statistics, or a related technical field; graduate level preferred.

• Profound knowledge of Databricks lakehouse architecture, Unity Catalog governance, workflow orchestration, and cost optimization.

• Capability to design systems that support multiple data science teams and production workloads.

• Strong foundation in distributed systems, ML infrastructure, and cloud architecture.

• Proven technical leadership across teams and organizations; ability to influence without direct authority.

• Expertise in 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 in integrating LLM workflows into enterprise platforms is a plus.

• Contributions to open source ML infrastructure projects or research publications are highly regarded.

🏝️ Benefits

• Equity

• Comprehensive benefits

• Competitive pay

• Access to the latest enterprise AI tools

• Flexible remote work options for up to 4 weeks per year for hybrid in-office roles

• Equal access to opportunities, growth, and success

• Reasonable accommodations throughout the recruitment process