Senior Machine Learning Engineer, Premium Discovery

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. Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running .

Posted 10/23/2026full-timeSan Francisco • California • United StatesSenior💰 $170,000 - $265,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining production ML systems, particularly in recommendation algorithms and large-scale data processing. Proficient in cloud deployment and cross-team collaboration to drive project success.

Highest-signal resume keywords

Production ML Systems DevelopmentRecommender Systems EngineeringLarge-Scale Data ProcessingCloud Deployment (AWS or GCP)A/B Testing Design and Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Collaborative FilteringMatrix FactorizationTwo-Tower RetrievalLearned RankingPythonFastAPIDjangoSparkBigQueryKubernetes

Soft Skills

Project LeadershipCross-Team CollaborationCommunication

Tools & Technologies

Google CloudVertex AIAWS SageMakerDatabricksAirflowElasticsearchTerraformDatadogECSSQS

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science

Industry Keywords

Recommendation SystemsSocial SignalsOnline ExperimentsConsumer AppsGraph-Based Recommendations

Tech Stack

Tools & technologies

AirflowAWSBigQueryCloudDjangoElasticSearchGoogle Cloud PlatformGRPCKubernetesPostgresPythonRubyRuby on RailsSparkTerraformGo

About the role

Key responsibilities & impact

Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's 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 health of Fable's recommendation systems in production, including quality, latency, cost and on-call
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 decide what ships
Act as technical lead for Premium recommendations, shape the roadmap with product managers, and drive cross-team delivery
Raise engineering practice through design reviews, code quality and operational readiness
Work with Fable's Python, FastAPI, Django, PostgreSQL, BigQuery, Kubernetes, Google Cloud and Vertex AI stack
Work with Orion and Everand's Python, Go, gRPC, Ruby on Rails, Databricks, Spark, Airflow, AWS SageMaker, Weaviate, feature store and model registry stack
Work with infrastructure including AWS EKS, ECS, Lambda, SQS, ElastiCache, Datadog and Terraform

Requirements

What you’ll need

5+ years as a professional ML or software engineer, with a track record of shipping production ML systems
Hands-on experience building and running recommender systems in production, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking
Experience with large-scale data processing (Spark, Databricks, BigQuery or similar)
Experience on at least one major cloud (AWS or GCP), including deploying services on containers (Kubernetes, ECS or similar)
Experience designing and analyzing online experiments
A record of leading projects that depend on other teams, and of working directly with product managers
Bachelor's or Master's degree in Computer Science, or equivalent professional experience
Nice to have: Google Cloud experience, especially Vertex AI and BigQuery
Nice to have: Experience migrating or replacing a production ML system while keeping it running
Nice to have: Social or graph-based recommendations, such as user similarity, follows or groups
Nice to have: Search and semantic retrieval (Elasticsearch, Vertex AI Search, vector databases)
Nice to have: Experience on consumer apps for reading, media or social
Primary residence in or near an eligible city in the United States, Canada, or Mexico
Ability to work in the country in which the position is based

Benefits

Comp & perks

Scribd Flex (flexible work model)
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
Occasional in-person attendance and intentional in-person moments