Scribd, Inc.
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Senior Machine Learning Engineer
role at
Scribd, Inc.
Overview At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.
About The Team Our Machine Learning team builds both the platform and product applications that power personalized discovery, recommendations, and generative AI features across Scribd, Slideshare, and Everand. The ML team works on the Orion ML Platform — providing core ML infrastructure, including a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). The MLE team also works closely with Product teams—delivering zero-to-one integrations of ML into user-facing features like recommendations, near real-time personalization, and AskAI LLM-powered experiences.
Role Overview We are seeking a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high-impact ML systems that serve millions of users in near real time. In this role, you will:
Drive technical direction for both platform and product-facing ML initiatives.
Lead complex, cross-team projects from conception to production deployment.
Mentor other engineers and establish best practices for building scalable, reliable ML systems.
Influence the roadmap and architecture of our ML Platform.
Tech Stack Our Machine Learning team uses a range of technologies to build and operate large-scale ML systems. Our regular toolkit includes:
Languages: Python, Golang, Scala, Ruby on Rails
Orchestration & Pipelines: Airflow, Databricks, Spark
ML & AI: AWS Sagemaker, embedding-based retrieval (Weaviate), feature store, model registry, model serving platforms, LLM providers like OpenAI, Anthropic, Gemini, etc.
APIs & Integration: HTTP APIs, gRPC
Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform
Key Responsibilities
Lead the design and architecture of ML pipelines, from data ingestion and feature engineering to model training, deployment, and monitoring.
Own the technical direction of core ML Platform components such as the feature store, model registry, and embedding-based retrieval systems.
Collaborate with product software engineers to deliver ML models that enhance recommendations, personalization, and generative AI features.
Guide experimentation strategy, A/B testing design, and performance analysis to inform production decisions.
Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services.
Establish and uphold engineering best practices, including code quality, system design reviews, and operational excellence.
Mentor and coach ML engineers, fostering technical growth and collaboration across the team.
Work with leadership to align technical initiatives with long-term ML strategy.
Requirements Must Have
6+ years of experience as a professional ML or software engineer, with a proven track record of delivering production ML systems at scale.
Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered).
Expertise in designing and architecting large-scale ML pipelines and distributed systems.
Deep experience with distributed data processing frameworks (Spark, Databricks, or similar).
Strong cloud expertise (AWS, Azure, or GCP) and experience with deployment platforms (ECS, EKS, Lambda).
Proven ability to optimize system performance and make informed trade-offs in ML model and system design.
Experience leading technical projects and mentoring engineers.
Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.
Nice to Have
Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems.
Experience building or leading development of feature stores, model serving & monitoring platforms, and experimentation systems.
Expertise in experimentation design, causal inference, or ML evaluation methodologies.
Contributions to open-source ML/AI tooling or infrastructure.
Why Join Us As a Senior ML Engineer at Scribd, you will shape the future of our ML systems, from foundational platform capabilities to cutting-edge AI applications. You’ll work with rich multimodal data (text, audio, images), state-of-the-art retrieval and recommendation technologies, and partner with a talented, cross-functional team to deliver personalized, impactful experiences for millions of users.
At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In California, the reasonably expected salary range is between $146,500 and $228,000. In the United States outside of California, the range is between $120,000 and $217,000. In Canada, the range is between $153,000 CAD and $202,000 CAD. We carefully consider a wide range of factors when determining compensation, including experience, skill sets, education, and other business needs. This position is eligible for equity and a comprehensive benefits package.
Are you based in a Scribd eligible location? Employees must have their primary residence in or near one of the following cities (surrounding metro areas or within typical commuting distance):
United States: 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.
Canada: Ottawa, Toronto, Vancouver
Mexico: Mexico City
Benefits, Perks, And Wellbeing
Benefits/perks listed may vary depending on location and employment type.
Healthcare Insurance Coverage (Medical/Dental/Vision): 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
Quarterly stipend for Wellness, WiFi, etc.
Mental Health resources
Free subscription to the Scribd Inc. suite of products
Referral Bonuses
Book Benefit
Sabbaticals
Company-wide events
Team engagement budgets
Vacation & Personal Days
Paid Holidays (+ winter break)
Flexible Sick Time
Volunteer Day
Inclusive workplace programs and ERGs
Access to AI Tools: free access to AI tools to boost productivity
We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process.
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, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Software Development
#J-18808-Ljbffr
Senior Machine Learning Engineer
role at
Scribd, Inc.
Overview At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.
About The Team Our Machine Learning team builds both the platform and product applications that power personalized discovery, recommendations, and generative AI features across Scribd, Slideshare, and Everand. The ML team works on the Orion ML Platform — providing core ML infrastructure, including a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). The MLE team also works closely with Product teams—delivering zero-to-one integrations of ML into user-facing features like recommendations, near real-time personalization, and AskAI LLM-powered experiences.
Role Overview We are seeking a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high-impact ML systems that serve millions of users in near real time. In this role, you will:
Drive technical direction for both platform and product-facing ML initiatives.
Lead complex, cross-team projects from conception to production deployment.
Mentor other engineers and establish best practices for building scalable, reliable ML systems.
Influence the roadmap and architecture of our ML Platform.
Tech Stack Our Machine Learning team uses a range of technologies to build and operate large-scale ML systems. Our regular toolkit includes:
Languages: Python, Golang, Scala, Ruby on Rails
Orchestration & Pipelines: Airflow, Databricks, Spark
ML & AI: AWS Sagemaker, embedding-based retrieval (Weaviate), feature store, model registry, model serving platforms, LLM providers like OpenAI, Anthropic, Gemini, etc.
APIs & Integration: HTTP APIs, gRPC
Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform
Key Responsibilities
Lead the design and architecture of ML pipelines, from data ingestion and feature engineering to model training, deployment, and monitoring.
Own the technical direction of core ML Platform components such as the feature store, model registry, and embedding-based retrieval systems.
Collaborate with product software engineers to deliver ML models that enhance recommendations, personalization, and generative AI features.
Guide experimentation strategy, A/B testing design, and performance analysis to inform production decisions.
Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services.
Establish and uphold engineering best practices, including code quality, system design reviews, and operational excellence.
Mentor and coach ML engineers, fostering technical growth and collaboration across the team.
Work with leadership to align technical initiatives with long-term ML strategy.
Requirements Must Have
6+ years of experience as a professional ML or software engineer, with a proven track record of delivering production ML systems at scale.
Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered).
Expertise in designing and architecting large-scale ML pipelines and distributed systems.
Deep experience with distributed data processing frameworks (Spark, Databricks, or similar).
Strong cloud expertise (AWS, Azure, or GCP) and experience with deployment platforms (ECS, EKS, Lambda).
Proven ability to optimize system performance and make informed trade-offs in ML model and system design.
Experience leading technical projects and mentoring engineers.
Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.
Nice to Have
Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems.
Experience building or leading development of feature stores, model serving & monitoring platforms, and experimentation systems.
Expertise in experimentation design, causal inference, or ML evaluation methodologies.
Contributions to open-source ML/AI tooling or infrastructure.
Why Join Us As a Senior ML Engineer at Scribd, you will shape the future of our ML systems, from foundational platform capabilities to cutting-edge AI applications. You’ll work with rich multimodal data (text, audio, images), state-of-the-art retrieval and recommendation technologies, and partner with a talented, cross-functional team to deliver personalized, impactful experiences for millions of users.
At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In California, the reasonably expected salary range is between $146,500 and $228,000. In the United States outside of California, the range is between $120,000 and $217,000. In Canada, the range is between $153,000 CAD and $202,000 CAD. We carefully consider a wide range of factors when determining compensation, including experience, skill sets, education, and other business needs. This position is eligible for equity and a comprehensive benefits package.
Are you based in a Scribd eligible location? Employees must have their primary residence in or near one of the following cities (surrounding metro areas or within typical commuting distance):
United States: 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.
Canada: Ottawa, Toronto, Vancouver
Mexico: Mexico City
Benefits, Perks, And Wellbeing
Benefits/perks listed may vary depending on location and employment type.
Healthcare Insurance Coverage (Medical/Dental/Vision): 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
Quarterly stipend for Wellness, WiFi, etc.
Mental Health resources
Free subscription to the Scribd Inc. suite of products
Referral Bonuses
Book Benefit
Sabbaticals
Company-wide events
Team engagement budgets
Vacation & Personal Days
Paid Holidays (+ winter break)
Flexible Sick Time
Volunteer Day
Inclusive workplace programs and ERGs
Access to AI Tools: free access to AI tools to boost productivity
We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process.
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, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Software Development
#J-18808-Ljbffr