Senior Machine Learning Engineer (Search)

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.

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.

So what are we looking for in new team members? 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.

This posting reflects an approved, open position within the organization.

About the team

The Search team powers personalized discovery across Scribd’s products, delivering relevant and engaging suggestions to millions of users. We operate at the intersection of large-scale data, cutting-edge machine learning, and product innovation — collaborating across brands and platforms to enhance user experiences in reading, listening, and learning. Our team is a blend of frontend, backend, and ML engineers who partner closely with product managers, data scientists, and analysts.

About the Role

We’re looking for a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high-impact ML discovery features that serve millions of users in near real time. You’ll work across the entire lifecycle — from data ingestion to model training, deployment, and monitoring — with a focus on creating fast, reliable, and cost-efficient pipelines. In this role, you will:

• Lead complex, cross-team projects from conception to production deployment.

• Drive technical direction for end-to-end, production-grade ML systems for advanced search capabilities and document understanding.

• Develop and operate services that power high-traffic pipelines for content discovery and knowledge synthesis.

• Run large-scale A/B and multivariate experiments to validate models and feature improvements.

• Mentor other engineers and establish best practices for building scalable, reliable ML systems.

Tech Stack

Our Machine Learning Engineers use 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 (Weights and Biases), 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

• Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry-standard frameworks.

• Collaborate with engineering and analytics teams to build large-scale ingestion, transformation, and validation pipelines on Databricks.

• Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services.

• Design and run A/B and N-way experiments to measure the impact of model and feature changes.

• Partner with product managers, data scientists, and analysts to identify opportunities, define requirements, and deliver solutions that solve real user problems.

Requirements

• 6+ years of experience as a professional ML engineer 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 (preferably GCP; also AWS and/or Azure) and experience with deployment platforms (ECS, EKS, Lambda).

• Experience with embedding-based retrieval, large language models, advanced information retrieval and ranking systems.

• Experience working with Search systems like query parsing, query intent classification, bm25, reranking, etc.

• 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.

At Scribd, Inc., 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 $157,500 [minimum salary in our lowest geographic market within California] to $230,000 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $129,500 [minimum salary in our lowest US geographic market outside of California] to $220,000 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $165,000 CAD[minimum salary in our lowest geographic market] to $218,000 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.

Are you currently based in a location where Scribd, Inc. can 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 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

Get to Know Scribd, Inc.
About Scribd, Inc.
Life at Scribd, Inc.

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, 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.