Software Engineer (Backend, Python) - Content Understanding …, Toronto

The ML Content Understanding Team

The ML Content Understanding team powers metadata extraction, enrichment, and content understanding across all Scribd brands. We process hundreds of millions of documents and billions of images to deliver high‑quality metadata that enables content discovery and trust for millions of users worldwide.Role Overview

We are seeking a Software Engineer II with strong backend development experience to design, build, and optimize distributed systems that extract, enrich, and process metadata for a wide range of content. The role involves working closely 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 at a global scale.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 such as 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 such as 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 skilled experience.Bonus: Experience working with LLMs or integrating ML models into production systems. Compensation

In California, the reasonable expected salary range for this role is between $126,000 and $196,000. In the United States outside of California, the range is between $103,500 and $186,500. In Canada, the range is between $131,500 CAD and $174,500 CAD. Compensation also includes competitive equity ownership and a comprehensive benefits package.Location Eligibility&Work Model

The position requires employees to have their primary residence in or near one of the following cities: 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., Ottawa, Toronto, Vancouver, or Mexico City. Scribd Flex provides a flexible work model, and occasional in‑person attendance is required.Benefits

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 equityLearning 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 EEO Statement

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.

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