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Senior Backend Engineer (Python)
Senior Backend Engineer (Python)Scribd, Inc. • Vancouver, Metro Vancouver Regional District, CA
Senior Backend Engineer (Python)

Senior Backend Engineer (Python)

Scribd, Inc. • Vancouver, Metro Vancouver Regional District, CA
Il y a plus de 30 jours
Type de contrat
  • Temps plein
Description de poste

Join to apply for the Senior Backend Engineer (Python + Distributed systems) role at Scribd, Inc.

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

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 Senior Software Engineer 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

  • Provide technical leadership, mentorship, and guidance to engineers across the organization, driving secure coding best practices.
  • Lead the design, implementation, and scaling of event‑driven, distributed systems to extract, enrich, and process metadata from large‑scale document and media datasets.
  • Partner with Data Science, Infrastructure, ML Engineering, and Product teams to architect and deliver robust systems that balance scalability, high performance, and rapid iteration.
  • Contribute to the team’s engineering strategy, identifying gaps, proposing new initiatives, and improving existing frameworks.
  • 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.
  • Optimize and refactor existing backend systems for scalability, reliability, and performance.
  • Ensure system health and data integrity through monitoring, observability, and automated testing.

Requirements

  • 7+ years of professional software engineering experience with a focus on backend or distributed systems development.
  • Strong proficiency in Python (5+ years). Experience with Scala is a plus.
  • Expertise in designing and architecting large‑scale event‑driven and distributed systems.
  • Strong cloud expertise 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.
  • Experience leading technical projects and mentoring engineers.
  • 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.
  • Compensation

    In the United States, salary ranges are : $146,500 to $228,000 in California (San Francisco) and $120,000 to $217,000 elsewhere. In Canada : 153,000 CAD to 202,000 CAD . The position is eligible for competitive equity and benefits.

    Benefits, Perks, and Wellbeing

  • Health insurance (100% paid for employees)
  • 12 weeks paid parental leave
  • Short‑term / long‑term disability plans
  • 401k / RSP matching
  • Onboarding stipend for home office peripherals
  • Learning & Development allowance and programs
  • Quarterly wellness stipend

  • Mental health support & resources
  • Free subscription to Scribd products
  • Referral bonuses
  • Book benefit
  • Sabbaticals
  • Company‑wide events
  • Team engagement budgets
  • Vacation & Personal Days
  • Paid holidays
  • Flexible sick time
  • Volunteer day
  • Employee Resource Groups and inclusive workplace programs
  • Access to AI tools
  • 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. Scribd 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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