Software Engineer; Backend, Python - Content Understanding

About the Team

The ML Content Understanding 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, audio books, 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.

We’re seeking a Software Engineer II with strong backend development experience and a passion for solving complex data challenges  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.

Python, Scala, Ruby on Rails, Airflow, Databricks, Spark, HTTP APIs, AWS (Lambda, ECS, SQS, Elasti Cache, Sage Maker, Cloud Watch, Datadog), and Terraform.

• 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.

• 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.
• 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.

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.

This position is also eligible for a competitive equity ownership and a comprehensive and generous benefits package.

Employees must 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

• Mexico City

• 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…