Senior Staff Machine Learning Platform Engineer

🕒 Agosto 14

🇨🇦 Canadá – Remoto

💵 $248.000 - $341.000 / ano

⏰ Tempo Integral

🟠 Sênior

🏗️ Engenheiro de Plataforma

👻 Score fantasma 8%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Faire

1001 - 5000 funcionários

Fundada em 2017

🤝 B2B

🛍️ Comércio Eletrônico

🛒 Varejo

B2B • eCommerce • Retail

A Faire é um mercado atacadista que conecta varejistas independentes a produtos exclusivos de marcas globais. Oferece uma plataforma para que varejistas descubram e comprem produtos que ressoem com seus clientes, apresentando várias categorias, incluindo itens de propriedade feminina, ecológicos e feitos à mão. Com benefícios como devoluções fáceis no primeiro pedido e opções de pagamento flexíveis, a Faire visa simplificar a experiência de compra para os varejistas, ao mesmo tempo em que apoia marcas diversas e locais.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

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

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