Scribd, Inc.
San Francisco, California
Company Overview Scribd, Inc. is on a mission to advance human understanding. Our four products - Scribd , Slideshare , Everand , and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be 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 believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture. Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location. At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. About The Team And Role Shape the core experience for 10M+ daily readers. Join the team behind Scribd's primary reading experience and directly impact how millions of users explore and learn from our 300,000+ document corpus. Experiment at the intersection of product and AI. Partner closely with Product, Design, and AI/ML teams to rapidly prototype and launch experiments that elevate engagement and comprehension on the document reading page. Build new creation experiences from 0 1. Help develop innovative tools that empower users to synthesize research and produce study guides, presentations, and documents - all enhanced by generative AI. Improve SEO and AEO. Work with our SEO PM to improve search and answer engine traffic to the Core Scribd pages. Modernize our tech stack for the future. Lead efforts to decompose our Ruby on Rails monolith into a modern, modular Microfrontend architecture powered by Next.js and a distributed backend. As a Senior Frontend Engineer on the Core Scribd team, you'll contribute to building and maintaining both the frontend powering Scribd's document reading page. You'll work on features that help users on a research journey find and parse the right document. This is a unique opportunity to work across a wide surface area from React based UI to distributed backend services in collaboration with product, design, AI/ML and infrastructure teams. A major focus for this team in 2026 is Web Modernization: migrating our legacy Doc Page SPA to a Next.js powered Microfrontend architecture, enabling faster iteration, safer scaling, and long term confidence in how Scribd's web product evolves. Key Attributes You are comfortable working cross functionally with PM, Data, Design, QE, MLE, backend engineers You can handle coordinating across backend teams, ML teams, data teams, and platform teams You have high customer empathy You build for the long term, you can reason about frontend architecture at scale You make trade offs based on available data, and you are able to communicate those trade offs/decisions clearly and succinctly Requirements Strong understanding of modern JavaScript frameworks, especially React. 5+ years of experience working across the front end stack, especially React. Familiarity of AWS cloud infrastructure and CI/CD pipelines. Understanding of performance, accessibility, and SEO principles across the stack. Strong collaboration skills, with the ability to work closely with design, product, and other engineering teams. A thoughtful approach to code quality, maintainability, and documentation. Compensation In the state of California, the reasonably expected salary range is between $146,000 (minimum salary in our lowest geographic market within California) to $227,500 (maximum salary in our highest geographic market within California). In the United States, outside of California, the reasonably expected salary range is between $120,000 (minimum salary in our lowest US geographic market outside of California) to $216,500 (maximum salary in our highest US geographic market outside of California). In Canada, the reasonably expected salary range is between $152,500 CAD (minimum salary in our lowest geographic market) to $194,500 CAD (maximum salary in our highest geographic market). This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a 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 At Scribd, Inc. 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 Equal Employment Opportunity 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 about the need for adjustments at any point in the interview process. Scribd, Inc. 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.
Company Overview Scribd, Inc. is on a mission to advance human understanding. Our four products - Scribd , Slideshare , Everand , and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be 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 believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture. Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location. At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. About The Team And Role Shape the core experience for 10M+ daily readers. Join the team behind Scribd's primary reading experience and directly impact how millions of users explore and learn from our 300,000+ document corpus. Experiment at the intersection of product and AI. Partner closely with Product, Design, and AI/ML teams to rapidly prototype and launch experiments that elevate engagement and comprehension on the document reading page. Build new creation experiences from 0 1. Help develop innovative tools that empower users to synthesize research and produce study guides, presentations, and documents - all enhanced by generative AI. Improve SEO and AEO. Work with our SEO PM to improve search and answer engine traffic to the Core Scribd pages. Modernize our tech stack for the future. Lead efforts to decompose our Ruby on Rails monolith into a modern, modular Microfrontend architecture powered by Next.js and a distributed backend. As a Senior Frontend Engineer on the Core Scribd team, you'll contribute to building and maintaining both the frontend powering Scribd's document reading page. You'll work on features that help users on a research journey find and parse the right document. This is a unique opportunity to work across a wide surface area from React based UI to distributed backend services in collaboration with product, design, AI/ML and infrastructure teams. A major focus for this team in 2026 is Web Modernization: migrating our legacy Doc Page SPA to a Next.js powered Microfrontend architecture, enabling faster iteration, safer scaling, and long term confidence in how Scribd's web product evolves. Key Attributes You are comfortable working cross functionally with PM, Data, Design, QE, MLE, backend engineers You can handle coordinating across backend teams, ML teams, data teams, and platform teams You have high customer empathy You build for the long term, you can reason about frontend architecture at scale You make trade offs based on available data, and you are able to communicate those trade offs/decisions clearly and succinctly Requirements Strong understanding of modern JavaScript frameworks, especially React. 5+ years of experience working across the front end stack, especially React. Familiarity of AWS cloud infrastructure and CI/CD pipelines. Understanding of performance, accessibility, and SEO principles across the stack. Strong collaboration skills, with the ability to work closely with design, product, and other engineering teams. A thoughtful approach to code quality, maintainability, and documentation. Compensation In the state of California, the reasonably expected salary range is between $146,000 (minimum salary in our lowest geographic market within California) to $227,500 (maximum salary in our highest geographic market within California). In the United States, outside of California, the reasonably expected salary range is between $120,000 (minimum salary in our lowest US geographic market outside of California) to $216,500 (maximum salary in our highest US geographic market outside of California). In Canada, the reasonably expected salary range is between $152,500 CAD (minimum salary in our lowest geographic market) to $194,500 CAD (maximum salary in our highest geographic market). This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a 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 At Scribd, Inc. 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 Equal Employment Opportunity 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 about the need for adjustments at any point in the interview process. Scribd, Inc. 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.
Scribd, Inc.
San Francisco, California
Scribd, Inc. is on a mission to advance human understanding. Our four products - Scribd , Slideshare , Everand , and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be 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 believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture. Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location. 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. 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, the reasonably expected salary range for this role in San Francisco is $146,500 to $228,000. Outside California, the range is $120,000 to $217,000. In Canada, the range is $153,000 CAD to $202,000 CAD. Compensation is determined within a range and may vary based on geographic market and experience. This position is eligible for equity ownership and a comprehensive benefits package. Working at Scribd, Inc. Employees must have their primary residence in or near one of the following cities: 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 At Scribd, Inc. 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 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 at any point in the interview process. Scribd, Inc. 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.
Scribd, Inc. is on a mission to advance human understanding. Our four products - Scribd , Slideshare , Everand , and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be 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 believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in person moments that strengthen collaboration and culture. Occasional in person attendance is required for all Scribd, Inc. employees, regardless of location. 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. 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, the reasonably expected salary range for this role in San Francisco is $146,500 to $228,000. Outside California, the range is $120,000 to $217,000. In Canada, the range is $153,000 CAD to $202,000 CAD. Compensation is determined within a range and may vary based on geographic market and experience. This position is eligible for equity ownership and a comprehensive benefits package. Working at Scribd, Inc. Employees must have their primary residence in or near one of the following cities: 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 At Scribd, Inc. 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 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 at any point in the interview process. Scribd, Inc. 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.
Scribd, Inc.
Miami, Florida
Overview Join to apply for the Machine Learning Engineer role at Scribd, Inc.. About The Company 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 three products: Everand, Scribd, and Slideshare. We support a culture where our employees can be real and be 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. When it comes to workplace structure, we believe in balancing individual flexibility and community connections. It's through our flexible work benefit, Scribd Flex, that employees - in partnership with their manager - can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location. So what are we looking for in new team members? Well, we hire for "GRIT". The textbook definition of GRIT is demonstrating the intersection of passion and perseverance towards long term goals. At Scribd, we are inspired by the potential that this can unlock, and ask each of our employees to pursue a GRIT-ty approach to their work. In a tactical sense, GRIT is also a handy acronym that outlines the standards we hold ourselves and each other to. Here's what that means for you: we're looking for someone who showcases the ability to set and achieve Goals, achieve Results within their job responsibilities, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and attitude. 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. ML teams works on the Orion ML Platform - providing core ML infrastructure, including a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). MLE team also works closely with Product team - 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 Machine Learning Engineer II to help design, build, and optimize high-impact ML systems that serve millions of users in near real time. You will work on projects that span from improving our core ML platform to integrating models directly into the product experience. 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 Design, build, and optimize ML pipelines, including data ingestion, feature engineering, training, and deployment for large-scale, real-time systems. Improve and extend core ML Platform capabilities such as the feature store, model registry, and embedding-based retrieval services. Collaborate with product software engineers to integrate ML models into user-facing features like recommendations, personalization, and AskAI. Conduct model experimentation, A/B testing, and performance analysis to guide production deployment. 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 and uphold engineering best practices. Manage and maintain ML infrastructure in cloud environments, including deployment pipelines, security, and monitoring. Qualifications Must Have 3+ years of experience as a professional software or machine learning engineer. Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered). Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar. Experience working with systems at scale and deploying to production environments. Cloud experience (AWS, Azure, or GCP), including building, deploying, and optimizing solutions with ECS, EKS, or AWS Lambda. Strong understanding of ML model trade-offs, scaling considerations, and performance optimization. Bachelor's in Computer Science or equivalent professional experience. Nice to Have Experience with embedding-based retrieval, recommendation systems, ranking models, or large language model integration. Experience with feature stores, model serving & monitoring platforms, and experimentation systems. Familiarity with large-scale system design for ML. Compensation and Benefits 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 the state of California, the reasonably expected salary range is between $126,000 minimum salary in our lowest geographic market within California to $196,000 maximum salary in our highest geographic market within California . In the United States, outside of California, the reasonably expected salary range is between $T103,500 minimum salary in our lowest US geographic market outside of California to $186,500 maximum salary in our highest US geographic market outside of California . In Canada, the reasonably expected salary range is between $131,500 CAD minimum salary in our lowest geographic market to $174,500 CAD maximum salary in our highest geographic market . We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd Are you currently based in a location where Scribd is able to employ you? 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 At Scribd Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work. 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 + accessories Learning & Development allowance Learning & Development programs Quarterly stipend for Wellness, WiFi, etc. Mental Health support & 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 Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace. Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation. Want to learn more about life at Scribd? 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 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. Position Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development
Overview Join to apply for the Machine Learning Engineer role at Scribd, Inc.. About The Company 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 three products: Everand, Scribd, and Slideshare. We support a culture where our employees can be real and be 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. When it comes to workplace structure, we believe in balancing individual flexibility and community connections. It's through our flexible work benefit, Scribd Flex, that employees - in partnership with their manager - can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location. So what are we looking for in new team members? Well, we hire for "GRIT". The textbook definition of GRIT is demonstrating the intersection of passion and perseverance towards long term goals. At Scribd, we are inspired by the potential that this can unlock, and ask each of our employees to pursue a GRIT-ty approach to their work. In a tactical sense, GRIT is also a handy acronym that outlines the standards we hold ourselves and each other to. Here's what that means for you: we're looking for someone who showcases the ability to set and achieve Goals, achieve Results within their job responsibilities, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and attitude. 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. ML teams works on the Orion ML Platform - providing core ML infrastructure, including a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). MLE team also works closely with Product team - 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 Machine Learning Engineer II to help design, build, and optimize high-impact ML systems that serve millions of users in near real time. You will work on projects that span from improving our core ML platform to integrating models directly into the product experience. 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 Design, build, and optimize ML pipelines, including data ingestion, feature engineering, training, and deployment for large-scale, real-time systems. Improve and extend core ML Platform capabilities such as the feature store, model registry, and embedding-based retrieval services. Collaborate with product software engineers to integrate ML models into user-facing features like recommendations, personalization, and AskAI. Conduct model experimentation, A/B testing, and performance analysis to guide production deployment. 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 and uphold engineering best practices. Manage and maintain ML infrastructure in cloud environments, including deployment pipelines, security, and monitoring. Qualifications Must Have 3+ years of experience as a professional software or machine learning engineer. Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered). Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar. Experience working with systems at scale and deploying to production environments. Cloud experience (AWS, Azure, or GCP), including building, deploying, and optimizing solutions with ECS, EKS, or AWS Lambda. Strong understanding of ML model trade-offs, scaling considerations, and performance optimization. Bachelor's in Computer Science or equivalent professional experience. Nice to Have Experience with embedding-based retrieval, recommendation systems, ranking models, or large language model integration. Experience with feature stores, model serving & monitoring platforms, and experimentation systems. Familiarity with large-scale system design for ML. Compensation and Benefits 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 the state of California, the reasonably expected salary range is between $126,000 minimum salary in our lowest geographic market within California to $196,000 maximum salary in our highest geographic market within California . In the United States, outside of California, the reasonably expected salary range is between $T103,500 minimum salary in our lowest US geographic market outside of California to $186,500 maximum salary in our highest US geographic market outside of California . In Canada, the reasonably expected salary range is between $131,500 CAD minimum salary in our lowest geographic market to $174,500 CAD maximum salary in our highest geographic market . We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd Are you currently based in a location where Scribd is able to employ you? 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 At Scribd Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work. 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 + accessories Learning & Development allowance Learning & Development programs Quarterly stipend for Wellness, WiFi, etc. Mental Health support & 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 Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace. Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation. Want to learn more about life at Scribd? 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 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. Position Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development