Software Engineer II (Backend + Data pipelines)
About The Position
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. 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.
Requirements
- 5+ 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
Nice To Haves
- Experience working with LLMs or integrating ML models into production systems
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
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 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
