Senior Machine Learning Engineer, Premium Discovery

Scribd, Inc.•San Francisco, CA

1d•$140,000 - $265,000

About The Position

Scribd, Inc. is hiring a Senior Machine Learning Engineer for Premium’s Discovery squad, a small team of recommendation, search, applied research, and ML engineers focused on discovery for Everand and Fable. The role will own recommendations for Fable and grow into the technical lead for Premium recommendations. The first major project is migrating Fable’s existing collaborative-filtering recommender to Orion, Scribd’s ML platform, while keeping current recommendations running and creating a modern shared recommendation stack for Fable and Everand. The engineer will extend Orion’s ranking, feature-store, and embedding-retrieval capabilities to support Fable; incorporate Fable’s social signals into recommendations; and own the production health of Fable’s recommendation systems. They will partner with product managers, analysts, and the Orion ML platform team to shape the roadmap, run experiments, and deliver work spanning teams. The position works across Fable’s Google Cloud stack and Orion/Everand’s AWS stack, using technologies including Python, Go, gRPC, PostgreSQL, BigQuery, Kubernetes, Vertex AI, Databricks, Spark, Airflow, SageMaker, Weaviate, and Terraform. Scribd uses a flexible work model, with employees choosing a workstyle and location that supports their performance. Occasional in-person attendance is required for all employees. The role is open to candidates whose primary residence is in or near listed cities in the United States, Canada, or Mexico. Compensation varies by geographic location; the posting gives ranges for California, other U.S. locations, and Canada. The position is also eligible for equity and a benefits package.

Requirements

At least 5 years as a professional ML or software engineer, with a track record of shipping production ML systems.
Hands-on experience building and operating production recommender systems, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking.
Experience with large-scale data processing, such as Spark, Databricks, or BigQuery.
Experience with at least one major cloud platform (AWS or GCP), including deploying services in containers such as Kubernetes or ECS.
Experience designing and analyzing online experiments.
A record of leading projects that depend on other teams and working directly with product managers.
Bachelor’s or Master’s degree in Computer Science, or equivalent professional experience.

Nice To Haves

Google Cloud experience, especially Vertex AI and BigQuery.
Experience migrating or replacing a production ML system while keeping it running.
Experience with social or graph-based recommendations, such as user similarity, follows, or groups.
Experience with search and semantic retrieval, such as Elasticsearch, Vertex AI Search, or vector databases.
Experience working on consumer apps for reading, media, or social.

Responsibilities

Lead the migration of Fable’s recommendations onto Orion, covering data, features, training, serving, and experiments while keeping existing recommendations running.
Extend Orion’s rankers, feature store, and embedding-based retrieval to support Fable in partnership with the Orion ML platform team.
Own the production health of Fable’s recommendation systems, including quality, latency, cost, and on-call responsibilities.
Bring Fable’s social signals—including shelves, ratings, reviews, book clubs, and reader similarity—into recommendations for Fable and Everand.
Design and analyze A/B tests with product managers and analysts to determine what ships.
Act as technical lead for Premium recommendations, shape the roadmap with product managers, and deliver work that depends on other teams’ systems.
Raise engineering practices in the squad through design reviews, code quality, and operational readiness.

Benefits

Comprehensive health, dental, and vision coverage.
Mental health support and disability coverage.
Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals.
Paid parental leave and family support benefits.
Retirement matching and employee equity.
Learning and development programs and professional growth opportunities.
Wellness and home office stipends.
Complimentary access to the Scribd, Inc. suite of products.
Enterprise access to leading AI tools.
Competitive equity ownership and a comprehensive benefits package.