Scribd is looking to solve the problem of personalized discovery across its products by building and optimizing ML systems that scale to millions of users, with a focus on creating fast, reliable, and cost-efficient pipelines and delivering next-generation AI features.
Requirements
- Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered).
- Expertise in 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 with embedding-based retrieval, large language models, advanced recommendation or ranking systems.
- Expertise in experimentation design, causal inference, or ML evaluation methodologies.
Responsibilities
- Prototype 0 1* solutions in collaboration with product and engineering teams.
- Build and maintain end-to-end, production-grade ML systems* for recommendations, search, and generative AI features.
- Develop and operate services in Go, Python, and Ruby* that power high-traffic recommendation and personalization pipelines.
- Run large-scale A/B and multivariate experiments* to validate models and feature improvements.
- Transform Scribd’s massive, diverse dataset* into actionable insights that drive measurable business impact.
- Explore and implement generative AI* for conversational recommendations, document understanding, and advanced search capabilities.
- Collaborate with engineering and analytics teams to build large-scale ingestion, transformation, and validation pipelines on Databricks*.
Other
- 4+ years of post qualification experience as a professional ML or software engineer, with a proven track record of delivering production ML systems at scale.
- Experience leading technical projects and mentoring engineers.
- Occasional in-person attendance is required for all Scribd employees, regardless of their location.
- Primary residence in or near one of the specified cities in the United States, Canada, or Mexico.
- Ability to set and achieve Goals, achieve Results within their job responsibilities, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and attitude.
