Backend Software Engineer; Python

Overview

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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 four products:
Everand, Scribd, Slideshare, and Fable.

We support a culture where our employees can be real and 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 balance individual flexibility and community connections through Scribd Flex, a flexible work benefit that allows employees to choose a daily work-style in partnership with their manager.

Occasional in-person attendance is required for all Scribd employees, regardless of location.

We hire for “GRIT” — goals, results, innovation, and teamwork. We look for someone who can set and achieve goals, deliver results, contribute innovative ideas, and positively influence the team through collaboration and attitude.

About The Team - The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across Scribd brands. We process hundreds of millions of documents and billions of images to enable content discovery and trust for millions of users. Our systems operate at massive scale and support diverse datasets. We deploy scalable ML and LLM-powered solutions in production in collaboration with applied research and product teams.

We’re seeking a Software Engineer II with deep experience building event-driven, distributed, and scalable systems in Python. You’ll design and optimize large-scale data and service pipelines on AWS, supporting Scribd’s content enrichment and metadata systems. You’ll work 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 global scale.

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

• 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, Elasti Cache, Cloud Watch) 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.

• 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, Cloud Watch, 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, your base pay is one part of your total compensation package and is determined within a range based on local benchmarks. Salary ranges vary by geography:

• San Francisco area (CA): range is between $126,000 and $196,000
• United…