Scribd, Inc.
Software Engineer II (Backend + Data pipelines)
Scribd, Inc., San Diego, California, United States, 92189
Overview
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. When it comes to workplace structure, we believe in balancing individual flexibility and community connections. It’s through our flexible work benefit, Scribd Flex, that employees – in partnership with their manager – can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location. We hire for “GRIT” — Goals, Results, Innovation, and Team — and look for a GRIT-ty approach to work. The Team
The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across all 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 operate at massive scale, supporting diverse datasets like user-generated content, ebooks, audiobooks, and more. We work at the intersection of machine learning, data engineering, and distributed systems, collaborating with applied research and product teams to 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. In this role, you’ll design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. You’ll work closely with ML engineers, product managers, and cross-functional partners to integrate machine learning models and LLM-based services into production pipelines and deliver impactful, high-performance solutions. This role offers the opportunity to work on cutting-edge generative AI and metadata enrichment problems at a truly global scale. Tech Stack
Our team uses various technologies. The following are the ones that we use on a regular basis: 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, including ML engineers and product managers, 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, ensuring best practices are followed and maintaining 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 building, deploying, and optimizing solutions using ECS, EKS, or AWS Lambda Experience with infrastructure-as-code tools like Terraform (or similar) Experience working 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 working with LLMs or integrating ML models into production systems At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $126,000 and $196,000. In the United States, outside of California, the reasonably expected salary range is between $103,500 and $186,500. In Canada, the reasonably expected salary range is between $131,500 CAD and $174,500 CAD. We carefully consider a wide range of factors when determining compensation, including but not limited to experience, job-related skill sets, relevant education or training, and other business and organizational needs. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc.
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, including surrounding metro areas or locations within a typical commuting distance: 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 At Scribd
Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work. 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 + accessories Learning & Development allowance Learning & Development programs Quarterly stipend for Wellness, WiFi, 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 (+ winter break) Flexible Sick Time Volunteer Day Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace. Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation. Want to learn more about life at Scribd?
www.linkedin.com/company/scribd/life We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process.
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. Come join us in building something meaningful. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development Referrals increase your chances of interviewing at Scribd, Inc. by 2x Get notified about new Software Engineer jobs in San Diego, CA.
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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. When it comes to workplace structure, we believe in balancing individual flexibility and community connections. It’s through our flexible work benefit, Scribd Flex, that employees – in partnership with their manager – can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location. We hire for “GRIT” — Goals, Results, Innovation, and Team — and look for a GRIT-ty approach to work. The Team
The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across all 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 operate at massive scale, supporting diverse datasets like user-generated content, ebooks, audiobooks, and more. We work at the intersection of machine learning, data engineering, and distributed systems, collaborating with applied research and product teams to 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. In this role, you’ll design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. You’ll work closely with ML engineers, product managers, and cross-functional partners to integrate machine learning models and LLM-based services into production pipelines and deliver impactful, high-performance solutions. This role offers the opportunity to work on cutting-edge generative AI and metadata enrichment problems at a truly global scale. Tech Stack
Our team uses various technologies. The following are the ones that we use on a regular basis: 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, including ML engineers and product managers, 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, ensuring best practices are followed and maintaining 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 building, deploying, and optimizing solutions using ECS, EKS, or AWS Lambda Experience with infrastructure-as-code tools like Terraform (or similar) Experience working 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 working with LLMs or integrating ML models into production systems At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $126,000 and $196,000. In the United States, outside of California, the reasonably expected salary range is between $103,500 and $186,500. In Canada, the reasonably expected salary range is between $131,500 CAD and $174,500 CAD. We carefully consider a wide range of factors when determining compensation, including but not limited to experience, job-related skill sets, relevant education or training, and other business and organizational needs. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc.
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, including surrounding metro areas or locations within a typical commuting distance: 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 At Scribd
Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work. 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 + accessories Learning & Development allowance Learning & Development programs Quarterly stipend for Wellness, WiFi, 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 (+ winter break) Flexible Sick Time Volunteer Day Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace. Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation. Want to learn more about life at Scribd?
www.linkedin.com/company/scribd/life We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process.
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. Come join us in building something meaningful. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development Referrals increase your chances of interviewing at Scribd, Inc. by 2x Get notified about new Software Engineer jobs in San Diego, CA.
#J-18808-Ljbffr