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Scribd, Inc.

Scribd, Inc.

www.scribd.com

4 Jobs

398 Employees

About the Company

Scribd, Inc. is a multinational technology company focused on the written and spoken word. Our three brands -- Everand(tm), Scribd(r), and SlideShare(r) -- deliver knowledge, information, and inspiration to billions of people across the globe.

Listed Jobs

Company background Company brand
Company Name
Scribd, Inc.
Job Title
Backend Software Engineer (Python)
Job Description
Job Title: Backend Software Engineer (Python) Role Summary: Design, build, and maintain event‑driven, distributed data and service pipelines in Python on AWS. Deliver scalable backend services that process large‑scale document and media metadata, integrate machine learning and LLM models, and support high‑throughput content enrichment at global scale. Expectations: - Lead architecture decisions for scalable, reliable backend systems. - Interface with cross‑functional teams (data engineering, ML, product) to define backend requirements. - Deliver production‑grade code, observability, and automated testing. - Continuously optimize performance and cost. Key Responsibilities: - Build event‑driven services using AWS Lambda, ECS, SQS, and other services. - Develop and maintain scalable APIs for content processing workflows. - Deploy and manage infrastructure with Terraform and monitor with CloudWatch/Datadog. - Refactor existing systems for scalability, reliability, and performance. - Join cross‑team collaborations to integrate ML/LLM components and new features. - Ensure data integrity, observability, and automated testing coverage. Required Skills: - 5+ years professional Python software engineering experience. - Proficient in event‑driven, distributed systems design. - Hands‑on with AWS services (ECS, Lambda, SQS, SNS, CloudWatch, ElastiCache). - Experience with infrastructure‑as‑code (Terraform). - Strong system performance profiling and optimization skills. - Familiarity with workflow orchestration (Airflow) and data processing frameworks (Spark, Databricks) is a plus. - Ability to integrate ML or LLM models into production services is a bonus. Required Education & Certifications: - Bachelor’s degree in Computer Science, Information Systems, or equivalent professional experience. - No mandatory certifications required.
Toronto, Canada
Hybrid
Mid level
11-11-2025
Company background Company brand
Company Name
Scribd, Inc.
Job Title
Senior Machine Learning Engineer (Recommendations)
Job Description
**Job title:** Senior Machine Learning Engineer (Recommendations) **Role Summary:** Design, build, and optimize large‑scale machine learning systems for recommendation, search, and generative AI features that serve millions of users. Manage the full ML lifecycle—from data ingestion and feature engineering on Databricks, to model training, deployment, experimentation, and monitoring—focusing on speed, reliability, and cost efficiency. Deliver next‑generation AI experiences such as conversational recommendations and document‑understanding chatbots. **Expectations:** - Deliver production‑grade ML systems that operate at scale. - Optimize system performance and make trade‑offs in model and infrastructure design. - Lead technical projects, mentor peers, and collaborate cross‑functionally with product managers, data scientists, and analysts. - Drive measurable business impact through experimentation and data‑driven insights. **Key Responsibilities:** - Build and maintain large‑scale data ingestion, transformation, and validation pipelines on Databricks. - Develop, evaluate, and deploy ML models (including generative models) using internal platforms and industry frameworks. - Design and execute A/B and multivariate experiments to quantify model and feature improvements. - Partner with product, data science, and analytics teams to define requirements, identify opportunities, and deliver solutions that solve real user problems. **Required Skills:** - 4+ years of professional ML or software engineering experience with a proven record of deploying production ML at scale. - Strong proficiency in Python or Go (Scala or Ruby acceptable). - Deep expertise in designing large‑scale ML pipelines and distributed systems. - Extensive experience with Spark, Databricks, or comparable distributed data processing frameworks. - Cloud platform expertise (AWS, Azure, or GCP) and familiarity with ECS, EKS, Lambda, or similar deployment solutions. - Proven ability to optimize system performance and make informed trade‑offs. - Leadership experience and mentoring capabilities. **Required Education & Certifications:** - Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent professional experience.
Ottawa, Canada
Hybrid
Senior
20-11-2025
Company background Company brand
Company Name
Scribd, Inc.
Job Title
Senior Machine Learning Engineer
Job Description
Job Title: Senior Machine Learning Engineer Role Summary Lead the design, architecture, and optimization of large‑scale ML systems that power recommendation, personalization, and generative AI services for millions of users. Drive technical direction for both platform and product‑level initiatives, mentor junior engineers, and shape the long‑term architecture of the ML platform. Expectations * Deliver end‑to‑end production ML pipelines that are scalable, reliable, and maintainable. * Own core platform components such as feature store, model registry, and embedding‑based retrieval. * Collaborate with product and software teams to integrate ML models into user‑facing features. * Guide experimentation and data‑driven decision making. * Mentor and raise technical standards across the ML organization. Key Responsibilities 1. Design and build robust ML pipelines from data ingestion to model deployment and monitoring. 2. Own technical strategy for core platform services (feature store, registry, retrieval). 3. Partner with product engineers to ship recommendation, personalization, and LLM features. 4. Define and execute A/B testing, experimentation, and performance analysis. 5. Optimize systems for performance, scalability, and reliability. 6. Establish best practices: code quality, design reviews, operational excellence. 7. Coach and develop team members. 8. Align technical initiatives with long‑term ML strategy in collaboration with leadership. Required Skills * 6+ years of professional ML or software engineering experience at scale. * Proficiency in Python or Golang (Scala or Ruby acceptable). * Expertise in distributed data processing (Spark, Databricks, or equivalent). * Strong cloud skills (AWS, Azure, or GCP) and experience with ECS, EKS, Lambda, or similar. * Knowledge of ML tooling: SageMaker, feature stores, model registries, embedding‑based retrieval, LLM APIs (OpenAI, Anthropic, Gemini). * Familiarity with orchestration (Airflow), batch/spark pipelines, HTTP/gRPC APIs, and infrastructure as code (Terraform). * Experience with experiment design, A/B testing, and performance monitoring (Datadog, CloudWatch). Required Education & Certifications * Bachelor’s degree in Computer Science, Engineering, or related field (advanced degree preferred). * Relevant certifications such as AWS Certified Machine Learning – Specialty or equivalent are a plus.
Vancouver, Canada
Hybrid
Senior
20-11-2025
Company background Company brand
Company Name
Scribd, Inc.
Job Title
Machine Learning Engineer
Job Description
**Job title** Machine Learning Engineer II **Role Summary** Design, build, and optimize production‑grade machine learning pipelines and platform services that deliver real‑time AI features (e.g., recommendations, personalization, LLM-powered experiences) to millions of users. **Expactations** - Deliver end‑to‑end ML solutions with high performance, scalability, and reliability. - Collaborate cross‑functionally with product and software engineering teams to embed models into user‑facing features. - Conduct rigorous experimentation, A/B testing, and analytics to validate model impact. - Maintain and enhance core ML platform components (feature store, model registry, embedding‑based retrieval). **Key Responsibilities** - Build and optimize data ingestion, feature engineering, training, and serving pipelines using Python, Spark, Databricks, Airflow, and CI/CD tools. - Extend and improve the feature store, model registry, embedding-based retrieval, and model inference services. - Integrate trained models into product features (recommendations, personalization, AskAI) via HTTP/gRPC APIs. - Perform model experimentation, A/B testing, and runtime performance analysis. - Refactor and tune existing systems for scalability, reliability, and cost efficiency. - Implement automated data validation, monitoring, and alerting; maintain security and compliance. - Participate in code reviews, enforce best practices, and document solutions. **Required Skills** - 3+ years professional experience in software or machine learning engineering. - Strong proficiency in Python (or Golang); experience with Scala or Ruby acceptable. - Hands‑on design and deployment of ML pipelines using Spark, Databricks, or similar. - Experience with feature stores, model registries, and model serving at scale. - Cloud expertise in AWS (Lambda, ECS, EKS, SQS, CloudWatch, Terraform). - Familiarity with AWS SageMaker, embedding‑based retrieval (Weaviate), and large‑scale LLM integration (OpenAI, Anthropic, Gemini). - Knowledge of PR/SQL for data extraction, ML experiment tracking, and performance tuning. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent professional experience). - (Optional) Certifications such as AWS Certified Solutions Architect, TensorFlow Developer, or similar.
Vancouver, Canada
Hybrid
Junior
26-12-2025