Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd, Slideshare, Everand, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise.

Culture at Scribd, Inc.

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.

We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location.

So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude.

This posting reflects an approved, open position within the organization.

About 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.

Our systems operate at massive scale, supporting diverse datasets like user-generated content (UGC), ebooks, audiobooks, and more. We work at the intersection of machine learning, data engineering, and distributed systems, collaborating closely 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 deep experience building event-driven, distributed, and scalable systems in Python. In this role, you’ll design and optimize large-scale data and service pipelines running on AWS, supporting Scribd’s content enrichment and metadata systems. You’ll work closely with cross-functional teams to design reliable backend services that integrate machine learning models and LLM-based components when needed. This role offers the opportunity to work on cutting-edge generative AI and metadata enrichment problems at a truly global scale.

Tech Stack:

Our backend systems are primarily built in Python, leveraging AWS services such as Lambda, ECS, SQS, and ElastiCache for event-driven and distributed processing. We also use Airflow, Spark, Databricks, Terraform, and Datadog for orchestration, data processing, and observability.

Key Responsibilities:

• Design and implement event-driven, distributed systems to extract, enrich, and process metadata from large-scale document and media datasets.

• Build and maintain scalable APIs and backend services for high-throughput content processing.

• Leverage AWS services (ECS, Lambda, SQS, ElastiCache, CloudWatch) to design and deploy resilient, high-performance systems.

• Collaborate with cross-functional teams to deliver backend solutions that power ML-driven features.

• Optimize and refactor existing backend systems for scalability, reliability, and performance.

• Ensure system health and data integrity through monitoring, observability, and automated testing.

Requirements:

• 5+ years of professional software engineering experience on Python or distributed systems development.

• Strong proficiency in Python (3+ years). Experience with Scala is a plus.

• Proven experience designing and building event-driven, distributed, and scalable systems.

• Hands-on experience with AWS services (ECS, Lambda, SQS, SNS, CloudWatch, etc.).

• Experience with infrastructure-as-code tools like Terraform.

• Solid understanding of system performance, profiling, and optimization.

• Bachelor’s degree in Computer Science or equivalent professional experience.

• Bonus: Familiarity with data processing frameworks (Spark, Databricks) and workflow orchestration tools.

• Bonus: Experience integrating ML or LLM-based models into production systems.

At Scribd, Inc., 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 [minimum salary in our lowest geographic market within California] to $196,000 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $103,500 [minimum salary in our lowest US geographic market outside of California] to $186,500 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $131,500 CAD[minimum salary in our lowest geographic market] to $174,500 CAD[maximum salary in our highest geographic market].

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. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. 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, Inc. can employ you?
Employees must have their primary residence in or near one of the following cities. This includes 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 at Scribd, Inc.

• Scribd Flex (flexible work model)

• Comprehensive health, dental, and vision coverage

• Mental health support and disability coverage

• Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals

• Paid parental leave and family support benefits

• Retirement matching and employee equity

• Learning and development programs and professional growth opportunities

• Wellness and home office stipends

• Complimentary access to the Scribd, Inc. suite of products

• Enterprise access to leading AI tools

Get to Know Scribd, Inc.
About Scribd, Inc.
Life at Scribd, Inc.

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.

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Scribd, Inc. 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.