Who you are

• 10-12 years of experience building and improving large-scale ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization
• Proven ability to design systems that support multiple data science teams and production workloads
• Strong background in distributed systems, ML infrastructure, and cloud architecture
• Demonstrated technical leadership across teams and orgs; ability to influence without authority
• Experience integrating LLM workflows into enterprise platforms is a plus
• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus
• Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following:
• Python, SQL, Kotlin, PyTorch, PySpark, MLFlow, Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL, AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform, Claude Sonnet 4.5, ChatGPT 5.2

What the job involves

• As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale
• This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses
• Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, 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 ahead of the curve by engaging with the latest developments in machine learning and AI
• Serve as senior ML technical advisor to Faire’s data science and production engineering teams
• Represent Faire at ML conferences and meetups
• Mentor ML engineers and raise the overall bar for Machine Learning at Faire

Benefits

• Comprehensive healthcare: Including Health, Dental, Vision and Disability for all our locations.
• Time off: Paid time off, holidays and company-wide "Faire Fundays".
• Parental leave: Generous parental and family leave, as well as fertility support benefits.
• Productivity support: Monthly stipends to help cover work from home connectivity needs.
• Annual learning grant: For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning.
• Thoughtfully designed spaces: All of our offices have been designed with local in mind – from our architects to our coffee blends.
• Fitness and well-being benefits: Including monthly credit towards your wellness-related programmes.
• Mental health benefits: Including free access to Modern Health therapists and resources.
• Charitable matching: Faire will match up to £250 of your charity donations, every year.
• Career planning: Whether you want to grow as a leader, hone your craft or explore a new discipline, our career framework allows space for you to explore.