Senior Machine Learning Engineer

OverviewJoin to apply for the Senior Machine Learning Engineer - Discovery (ML + Backend Engineering) role at Scribd, Inc.We are looking for a Machine Learning Engineer who will design, build, and optimize ML systems that scale to millions of users, with a focus on fast, reliable, and cost-efficient pipelines and next-generation AI features.About The CompanyAt Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our products: Everand, Scribd, and Slideshare.We support a culture where employees can be real and bold, debate and commit, and take action while prioritizing the customer. Scribd Flex allows flexible work styles while prioritizing intentional in-person collaboration. Occasional in-person attendance is required for all Scribd employees, regardless of location.We hire for “GRIT” — Goals, Results, Innovative ideas, and Team collaboration and attitude. The Recommendations team powers personalized discovery across Scribd’s products, delivering relevant suggestions at scale through a blend of frontend, backend, and ML engineering collaboration.ResponsibilitiesData Pipelines – Collaborate to build large-scale ingestion, transformation, and validation pipelines on Databricks.Model Development & Deployment – Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and standard frameworks.Experimentation – Design and run A/B and N-way experiments to measure impact of model and feature changes.Cross-Functional Collaboration – Partner with product managers, data scientists, and analysts to identify opportunities and deliver solutions that solve real user problems.RequirementsMust Have4+ years of post-qualification experience as a professional ML or software engineer, with a proven track record of delivering production ML systems at scale.Proficiency in Python, Go, or similar languages (Scala or Ruby also considered).Experience designing and architecting large-scale ML pipelines and distributed systems.Deep experience with distributed data processing frameworks (Spark, Databricks, or similar).Strong cloud expertise (AWS, Azure, or GCP) and experience with deployment platforms (ECS, EKS, Lambda).Proven ability to optimize system performance and make informed trade-offs in ML model and system design.Experience leading technical projects and mentoring engineers.Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.Nice to HaveExperience with embedding-based retrieval, large language models, advanced recommendation or ranking systems.Expertise in experimentation design, causal inference, or ML evaluation methodologies.Role HighlightKey responsibilities include data pipelines, model development and deployment, experimentation, and cross-functional collaboration to deliver end-to-end ML-powered features such as doc-chat and ask-AI for Scribd’s content.Benefits & Working at ScribdHigh-Impact Environment: Power recommendations, search, and AI features used by millions.Cutting-Edge Projects: Tackle challenging ML/AI problems with a forward-thinking team.Collaborative Culture and Flexible Workplace: Scribd Flex with emphasis on in-person collaboration.Comprehensive benefits, including healthcare, parental leave, disability plans, 401k/RSP matching, learning allowances, wellness stipends, and more.Note: Working at Scribd compensation includes base pay and benefits; ranges vary by location. This position is eligible for equity and a comprehensive benefits package.Are you based in a location where Scribd can employ you? Primary residence should be in or near United States (cities listed), Canada (cities listed), or Mexico City for eligibility.Equal OpportunityScribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply. #J-18808-Ljbffr