Senior Machine Learning Engineer

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 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 the state of California, the reasonably expected salary range is between $146,500 [minimum salary in our lowest geographic market within California] to $228,000 [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 $217,000 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $153,000 CAD[minimum salary in our lowest geographic market] to $202,000 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, inc.

Are you currently based in a location where Scribd is able to employ you?
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, 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? www.linkedin.com/company/scribd/life

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 [email protected] 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.