Scribd, Inc.
Software Engineer II (Backend + Data pipelines)
Scribd, Inc., Boston, Massachusetts, us, 02298
Join to apply for the
Software Engineer II (Backend + Data pipelines)
role at
Scribd, Inc.
Get AI-powered advice on this job and more exclusive features.
About The Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.
We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. Scribd Flex enables flexible work in partnership with managers, with occasional in-person attendance required for all Scribd employees, regardless of location.
We hire for “GRIT”—Goals, Results, Innovation, and Team. We value setting and achieving goals, delivering results, contributing innovative ideas, and positively influencing the team through collaboration and attitude.
The Team The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across Scribd brands. We process hundreds of millions of documents, billions of images, and deliver high-quality metadata to enable content discovery and trust for millions of users worldwide. We work at scale across diverse datasets and deploy scalable ML and LLM-powered solutions in production.
Role Overview We’re seeking a
Software Engineer II
with strong backend development experience and a passion for solving complex data challenges at scale. You’ll design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. You’ll work with ML engineers, product managers, and cross-functional partners to integrate machine learning models and LLM-based services into production pipelines and deliver high-performance solutions. This role offers exposure to cutting-edge generative AI and metadata enrichment problems at a global scale.
Tech Stack Python, Scala, Ruby on Rails, Airflow, Databricks, Spark, HTTP APIs, AWS (Lambda, ECS, SQS, ElastiCache, Sagemaker, CloudWatch, Datadog) and Terraform.
Key Responsibilities
Design and build scalable systems to extract, enrich, and process metadata from millions of documents, images, and audio content.
Leverage LLMs to integrate capabilities like summarization, classification, extraction, and enrichment into metadata pipelines.
Collaborate with cross-functional teams to deliver scalable, efficient, and reliable metadata solutions.
Optimize and refactor existing systems for performance, scalability, and reliability.
Ensure data accuracy, integrity, and quality through automated validation and monitoring.
Participate in code reviews and maintain high-quality standards in the codebase.
Manage and maintain data pipelines, security, and infrastructure.
Requirements
4+ years of professional software engineering experience
Proficiency in Python, Scala, Ruby, or similar languages
Experience designing and building distributed systems at scale
Hands-on experience with ECS, EKS, or AWS Lambda
Experience with infrastructure-as-code tools like Terraform
Experience with a public cloud provider (AWS, Azure, or Google Cloud)
Familiarity with data processing frameworks like Spark or Databricks for large-scale workloads
Proven ability to test, profile, and optimize systems for performance, scalability, and reliability
Bachelor’s degree in Computer Science or equivalent professional experience
Bonus: Experience with LLMs or integrating ML models into production systems
Compensation and Benefits At Scribd, your base pay is one part of your total compensation package and is determined within a range based on location and level. Salary ranges vary by geography and level. This position is eligible for a competitive equity package and a comprehensive benefits package. The ranges shown are examples and may differ for different levels and locations.
Working at Scribd Are you currently based in a location where Scribd is able to employ you? Employees must have their primary residence in or near one of the following cities and comparable commuting distances: United States — Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C.; Canada — Ottawa, Toronto, Vancouver; Mexico — Mexico City.
Benefits, Perks, And Wellbeing
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Disability plans
401k/RSP matching
Onboarding stipend for home office peripherals
Learning & Development allowances and programs
Wellness and connectivity stipends
Mental health resources
Free Scribd suite subscriptions
Referral bonuses and book benefit
Sabbaticals and company-wide events
Inclusive workplace with ERGs and AI tools access
EEO Statement 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 any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas.
For accessibility, you can request reasonable adjustments during the interview process by emailing accommodations@scribd.com.
#J-18808-Ljbffr
Software Engineer II (Backend + Data pipelines)
role at
Scribd, Inc.
Get AI-powered advice on this job and more exclusive features.
About The Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.
We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. Scribd Flex enables flexible work in partnership with managers, with occasional in-person attendance required for all Scribd employees, regardless of location.
We hire for “GRIT”—Goals, Results, Innovation, and Team. We value setting and achieving goals, delivering results, contributing innovative ideas, and positively influencing the team through collaboration and attitude.
The Team The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across Scribd brands. We process hundreds of millions of documents, billions of images, and deliver high-quality metadata to enable content discovery and trust for millions of users worldwide. We work at scale across diverse datasets and deploy scalable ML and LLM-powered solutions in production.
Role Overview We’re seeking a
Software Engineer II
with strong backend development experience and a passion for solving complex data challenges at scale. You’ll design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. You’ll work with ML engineers, product managers, and cross-functional partners to integrate machine learning models and LLM-based services into production pipelines and deliver high-performance solutions. This role offers exposure to cutting-edge generative AI and metadata enrichment problems at a global scale.
Tech Stack Python, Scala, Ruby on Rails, Airflow, Databricks, Spark, HTTP APIs, AWS (Lambda, ECS, SQS, ElastiCache, Sagemaker, CloudWatch, Datadog) and Terraform.
Key Responsibilities
Design and build scalable systems to extract, enrich, and process metadata from millions of documents, images, and audio content.
Leverage LLMs to integrate capabilities like summarization, classification, extraction, and enrichment into metadata pipelines.
Collaborate with cross-functional teams to deliver scalable, efficient, and reliable metadata solutions.
Optimize and refactor existing systems for performance, scalability, and reliability.
Ensure data accuracy, integrity, and quality through automated validation and monitoring.
Participate in code reviews and maintain high-quality standards in the codebase.
Manage and maintain data pipelines, security, and infrastructure.
Requirements
4+ years of professional software engineering experience
Proficiency in Python, Scala, Ruby, or similar languages
Experience designing and building distributed systems at scale
Hands-on experience with ECS, EKS, or AWS Lambda
Experience with infrastructure-as-code tools like Terraform
Experience with a public cloud provider (AWS, Azure, or Google Cloud)
Familiarity with data processing frameworks like Spark or Databricks for large-scale workloads
Proven ability to test, profile, and optimize systems for performance, scalability, and reliability
Bachelor’s degree in Computer Science or equivalent professional experience
Bonus: Experience with LLMs or integrating ML models into production systems
Compensation and Benefits At Scribd, your base pay is one part of your total compensation package and is determined within a range based on location and level. Salary ranges vary by geography and level. This position is eligible for a competitive equity package and a comprehensive benefits package. The ranges shown are examples and may differ for different levels and locations.
Working at Scribd Are you currently based in a location where Scribd is able to employ you? Employees must have their primary residence in or near one of the following cities and comparable commuting distances: United States — Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C.; Canada — Ottawa, Toronto, Vancouver; Mexico — Mexico City.
Benefits, Perks, And Wellbeing
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Disability plans
401k/RSP matching
Onboarding stipend for home office peripherals
Learning & Development allowances and programs
Wellness and connectivity stipends
Mental health resources
Free Scribd suite subscriptions
Referral bonuses and book benefit
Sabbaticals and company-wide events
Inclusive workplace with ERGs and AI tools access
EEO Statement 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 any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas.
For accessibility, you can request reasonable adjustments during the interview process by emailing accommodations@scribd.com.
#J-18808-Ljbffr