Scribd, Inc.
Senior Machine Learning Engineer (Search)
Scribd, Inc., San Francisco, California, United States, 94199
Senior Machine Learning Engineer (Search) – Scribd, Inc.
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Senior Machine Learning Engineer (Search)
role at
Scribd, Inc.
About the Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge by democratizing the exchange of ideas and information and empowering collective expertise through our four products: Everand, Scribd, Slideshare, and Fable.
We support a culture where employees can be real and bold, debate and commit as we embrace plot twists, and prioritize the customer. Our flexible work benefit, Scribd Flex, allows employees and managers to choose a daily work style that best suits individual needs, while intentional in‑person moments foster collaboration, culture, and connection.
We hire for “GRIT”. Our acronym stands for Goals, Results, Innovative ideas, and Team collaboration, and we look for candidates who demonstrate these principles.
About the Team The Search team powers personalized discovery across Scribd’s products, delivering relevant and engaging suggestions to millions of users. We operate at the intersection of large‑scale data, cutting‑edge machine learning, and product innovation, collaborating across brands and platforms to enhance user experiences in reading, listening, and learning.
About the Role We’re looking for a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high‑impact ML discovery features that serve millions of users in near real‑time. You’ll work across the entire lifecycle — from data ingestion to model training, deployment, and monitoring — with a focus on creating fast, reliable, and cost‑efficient pipelines.
Key Responsibilities
Lead complex, cross‑team projects from conception to production deployment.
Drive technical direction for end‑to‑end, production‑grade ML systems for advanced search capabilities and document understanding.
Develop and operate services that power high‑traffic pipelines for content discovery and knowledge synthesis.
Run large‑scale A/B and multivariate experiments to validate models and feature improvements.
Mentor other engineers and establish best practices for building scalable, reliable ML systems.
Tech Stack
Languages: Python, Golang, Scala, Ruby on Rails
Orchestration & Pipelines: Airflow, Databricks, Spark
ML & AI: AWS SageMaker, Embedding‑based Retrieval (Weaviate), Feature Store, Model Registry, Model Serving platforms (Weights & Biases), LLM providers like OpenAI, Anthropic, Gemini, etc.
APIs & Integration: HTTP APIs, gRPC
Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform
Requirements
6+ years of experience as a professional ML engineer or software engineer, with a proven track record of delivering production ML systems at scale.
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 (preferably GCP; also AWS and/or Azure) and experience with deployment platforms (ECS, EKS, Lambda).
Experience with embedding‑based retrieval, large language models, advanced information retrieval and ranking systems.
Experience working with Search systems like query parsing, query intent classification, bm25, reranking, etc.
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.
Compensation Base pay ranges from $157,500 to $230,000 in San Francisco, CA; $129,500 to $220,000 in other U.S. markets; and $165,000 CAD to $218,000 CAD in Canada. The salary range reflects local cost of labor benchmarks, experience, skill set, education, and other factors. This position is also eligible for competitive equity ownership and a comprehensive benefits package.
Working at Scribd, Inc. Are you currently based in a location where Scribd can employ you? Employees must have their primary residence in or near one of the following cities: Atlanta, Austin, Boston, Chicago, Dallas, Denver, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C. (U.S.); Ottawa, Toronto, Vancouver (Canada); Mexico City (Mexico). Employees may be required to attend occasional in‑person meetings.
Benefits, Perks, and Wellbeing at Scribd
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short‑term/long‑term disability plans
401k/RSP matching
Onboarding stipend for home office peripherals and accessories
Learning & Development allowance and programs
Quarterly stipend for wellness, Wi‑Fi, etc.
Mental Health support & resources
Free subscription to the Scribd Inc. suite of products
Referral bonuses
Book benefit
Sabbaticals
Company‑wide events
Team engagement budgets
Vacation & personal days
Paid holidays (including winter break)
Flexible sick time
Volunteer day
Company‑wide employee resource groups and programs fostering an inclusive and diverse workplace
Access to AI tools: free access to best‑in‑class AI tools to boost productivity and accelerate innovation
Legal Notice We want our interview process to be accessible to everyone. If you need reasonable adjustments, email accommodations@scribd.com. Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other characteristics protected by law. We encourage people of all backgrounds to apply, believing that diverse perspectives create a foundation for the best ideas. Come join us in building something meaningful.
#J-18808-Ljbffr
Senior Machine Learning Engineer (Search)
role at
Scribd, Inc.
About the Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge by democratizing the exchange of ideas and information and empowering collective expertise through our four products: Everand, Scribd, Slideshare, and Fable.
We support a culture where employees can be real and bold, debate and commit as we embrace plot twists, and prioritize the customer. Our flexible work benefit, Scribd Flex, allows employees and managers to choose a daily work style that best suits individual needs, while intentional in‑person moments foster collaboration, culture, and connection.
We hire for “GRIT”. Our acronym stands for Goals, Results, Innovative ideas, and Team collaboration, and we look for candidates who demonstrate these principles.
About the Team The Search team powers personalized discovery across Scribd’s products, delivering relevant and engaging suggestions to millions of users. We operate at the intersection of large‑scale data, cutting‑edge machine learning, and product innovation, collaborating across brands and platforms to enhance user experiences in reading, listening, and learning.
About the Role We’re looking for a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high‑impact ML discovery features that serve millions of users in near real‑time. You’ll work across the entire lifecycle — from data ingestion to model training, deployment, and monitoring — with a focus on creating fast, reliable, and cost‑efficient pipelines.
Key Responsibilities
Lead complex, cross‑team projects from conception to production deployment.
Drive technical direction for end‑to‑end, production‑grade ML systems for advanced search capabilities and document understanding.
Develop and operate services that power high‑traffic pipelines for content discovery and knowledge synthesis.
Run large‑scale A/B and multivariate experiments to validate models and feature improvements.
Mentor other engineers and establish best practices for building scalable, reliable ML systems.
Tech Stack
Languages: Python, Golang, Scala, Ruby on Rails
Orchestration & Pipelines: Airflow, Databricks, Spark
ML & AI: AWS SageMaker, Embedding‑based Retrieval (Weaviate), Feature Store, Model Registry, Model Serving platforms (Weights & Biases), LLM providers like OpenAI, Anthropic, Gemini, etc.
APIs & Integration: HTTP APIs, gRPC
Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform
Requirements
6+ years of experience as a professional ML engineer or software engineer, with a proven track record of delivering production ML systems at scale.
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 (preferably GCP; also AWS and/or Azure) and experience with deployment platforms (ECS, EKS, Lambda).
Experience with embedding‑based retrieval, large language models, advanced information retrieval and ranking systems.
Experience working with Search systems like query parsing, query intent classification, bm25, reranking, etc.
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.
Compensation Base pay ranges from $157,500 to $230,000 in San Francisco, CA; $129,500 to $220,000 in other U.S. markets; and $165,000 CAD to $218,000 CAD in Canada. The salary range reflects local cost of labor benchmarks, experience, skill set, education, and other factors. This position is also eligible for competitive equity ownership and a comprehensive benefits package.
Working at Scribd, Inc. Are you currently based in a location where Scribd can employ you? Employees must have their primary residence in or near one of the following cities: Atlanta, Austin, Boston, Chicago, Dallas, Denver, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C. (U.S.); Ottawa, Toronto, Vancouver (Canada); Mexico City (Mexico). Employees may be required to attend occasional in‑person meetings.
Benefits, Perks, and Wellbeing at Scribd
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short‑term/long‑term disability plans
401k/RSP matching
Onboarding stipend for home office peripherals and accessories
Learning & Development allowance and programs
Quarterly stipend for wellness, Wi‑Fi, etc.
Mental Health support & resources
Free subscription to the Scribd Inc. suite of products
Referral bonuses
Book benefit
Sabbaticals
Company‑wide events
Team engagement budgets
Vacation & personal days
Paid holidays (including winter break)
Flexible sick time
Volunteer day
Company‑wide employee resource groups and programs fostering an inclusive and diverse workplace
Access to AI tools: free access to best‑in‑class AI tools to boost productivity and accelerate innovation
Legal Notice We want our interview process to be accessible to everyone. If you need reasonable adjustments, email accommodations@scribd.com. Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other characteristics protected by law. We encourage people of all backgrounds to apply, believing that diverse perspectives create a foundation for the best ideas. Come join us in building something meaningful.
#J-18808-Ljbffr