Senior Staff Machine Learning Platform Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Define and steer the long-term architecture of Faire’s machine learning platform, encompassing training, inference, feature management, and governance.

• Set company-wide benchmarks 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 highly scalable machine learning workflows utilizing Spark, Delta Lake, and MLflow.

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

• Assess and incorporate emerging features from Databricks.

• Keep abreast of advancements in machine learning and artificial intelligence.

• Act as a senior ML technical advisor to data science and production engineering teams.

• Represent Faire at machine learning conferences and meetups.

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

⛳️ Requirements

• 10–12 years of experience in developing and enhancing large-scale machine learning or data platforms.

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

• Extensive expertise in Databricks lakehouse architecture, including Unity Catalog governance, Workflows orchestration, and cost optimization.

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

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

• Demonstrated technical leadership across teams and organizations; capable of influencing without direct authority.

• Proficient 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 or research publications are highly regarded.

🏝️ Benefits

• Equity

• Comprehensive benefits

• Competitive pay

• Access to the latest enterprise AI tools

• Equal access to opportunities, growth, and success

• Reasonable accommodations throughout the recruitment process