Senior Machine Learning Engineer

Overview

Join to apply for the Senior Machine Learning Engineer role at Scribd, Inc.

About The Company:

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 products:
Everand, Scribd, and Slideshare. We support a culture where employees can be real and bold, debate and commit, and prioritize the customer. Scribd Flex lets employees choose their daily work-style in partnership with their manager, with occasional in-person attendance required for all employees.

We hire for “GRIT”: setting and achieving Goals, achieving Results, contributing Innovative ideas, and positively influencing the Team through collaboration and attitude.

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.

Our Machine Learning team builds and operates large-scale ML systems across Scribd, Slideshare, and Everand. The ML Platform includes a feature store, model registry, model inference systems, and embedding-based retrieval (E ). The team collaborates with Product to deliver ML into user-facing features such as recommendations, near real-time personalization, and AskAI LLM-powered experiences.

• 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 (feature store, model registry, E ).
• Collaborate with product software engineers to deliver ML models that enhance recommendations and personalization.
• Guide experimentation strategy, A/B testing design, and performance analysis to inform production decisions.
• Optimize systems for performance, scalability, and reliability across large datasets and high-throughput services.
• Establish and uphold engineering best practices, including code quality, reviews, and operational excellence.
• Mentor and coach ML engineers, fostering technical growth and cross-team collaboration.
• Work with leadership to align technical initiatives with long-term ML strategy.

• 6+ years of experience as a professional ML or software engineer, delivering production ML systems at scale.
• Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered).
• Experience 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.

• 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.

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 and partner with a cross-functional team to deliver personalized, impactful experiences for millions of users.

Compensation:
The base pay ranges vary by location. California ranges: $146,500 to $228,000;…