Senior Machine Learning Engineer, Premium Discovery

Team and role

Key responsibilities

• Lead Fable’s recommendation migration to Orion across data, features, training, serving, and experiments while maintaining existing recommendations.
• Extend Orion rankers, feature store, and embedding retrieval to support Fable with the ML platform team.
• Own production quality, latency, cost, and on-call for Fable recommendation systems.
• Use Fable social signals, such as shelves, ratings, reviews, book clubs, and reader similarity, in recommendations for Fable and Everand.
• Design and analyze A/B tests with product managers and analysts.
• Lead Premium recommendation technical direction and roadmap delivery across teams.
• Raise engineering standards through design reviews, code quality, and operational readiness.

Technology

• Fable stack includes Python, FastAPI, Django, PostgreSQL, BigQuery, Kubernetes, and Google Cloud, including Vertex AI.
• Orion and Everand stack includes Python, Go, gRPC, Ruby on Rails, Databricks, Spark, Airflow, AWS SageMaker, and Weaviate.
• Infrastructure includes AWS services, Datadog, and Terraform.

Must-have qualifications

• 5+ years as a professional ML or software engineer and a record of shipping production ML systems.
• Hands-on production recommender experience, including methods such as collaborative filtering, matrix factorization, two-tower or embedding retrieval, and learned ranking.
• Experience with large-scale data processing such as Spark, Databricks, or BigQuery.
• Experience on AWS or GCP and deploying containerized services such as Kubernetes or ECS.
• Experience designing and analyzing online experiments.
• Experience leading cross-team projects and working directly with product managers.
• Bachelor’s or master’s degree in Computer Science, or equivalent professional experience.

Nice-to-have qualifications

• Google Cloud experience, especially Vertex AI and BigQuery.
• Experience migrating or replacing a production ML system while maintaining service.
• Experience with social or graph-based recommendations, search and semantic retrieval, or consumer reading, media, or social apps.

Pay

• In Canada, the stated salary range is CAD 179,000–237,500; compensation depends on role level, location, experience, skills, and other factors.
• The position is eligible for equity and benefits.

Work arrangements

• Employees choose a workstyle and location, with occasional in-person attendance required for all employees.
• Primary residence must be in or near an approved city; Vancouver is listed among eligible Canadian locations.

Benefits

• Benefits include health, dental, and vision coverage; mental health and disability support; paid time off and parental leave; retirement matching and equity; learning programs; wellness and home-office stipends; and product and AI-tool access.