Senior Machine Learning Engineer; Recommendations

Overview

Senior Machine Learning Engineer (Recommendations) responsible for designing, building, and optimizing ML systems that scale to millions of users. You will work across the entire lifecycle—from data ingestion to model training, deployment, and monitoring—with a focus on fast, reliable, and cost-efficient pipelines and the delivery of next-generation AI features.

Scribd (pronounced “scribbed”) is on a mission to spark human curiosity by democratizing access to stories and knowledge. The company supports a culture where employees can be bold, debate openly, and take action to prioritize the customer. Scribd Flex offers flexible daily work styles in partnership with managers, with a focus on intentional in-person collaboration.

The Recommendations team powers personalized discovery across Scribd’s products. We operate at the intersection of large-scale data, cutting-edge ML, and product innovation—collaborating across brands and platforms to enhance user experiences in reading, listening, and learning. Team members include frontend, backend, and ML engineers who partner with product managers, data scientists, and analysts.

We are seeking a machine learning engineer who will design, build, and optimize ML systems at scale, covering data ingestion, model training, deployment, and monitoring. You will contribute to next-generation AI features like doc-chat and ask-AI that expand how users interact with Scribd’s content.

• Data Pipelines – Collaborate with engineering and analytics teams to build large-scale ingestion, transformation, and validation pipelines on Databricks.
• Model Development & Deployment – Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry-standard frameworks.
• Experimentation – Design and run A/B and N-way experiments to measure the impact of model and feature changes.
• Cross-Functional Collaboration – Partner with product managers, data scientists, and analysts to identify opportunities, define requirements, and deliver solutions that solve real user problems.

• 4+ 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.

• Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems.
• Expertise in experimentation design, causal inference, or ML evaluation methodologies.

• High-Impact Environment:
  Your contributions will power recommendations, search, and next-generation AI features used by millions of readers, learners, and listeners worldwide.
• Cutting-Edge Projects:
  Tackle challenging ML and AI problems with a forward-thinking team, building novel generative features on top of Scribd’s data.
• Collaborative Culture:
  Join a culture that values debate, fresh perspectives, and continuous learning.
• Flexible Workplace:
  Benefit from Scribd Flex, prioritizing in-person collaboration while offering daily work-style autonomy.

Salary ranges vary by location. In the United States (California) the expected salary range is $120,000 to $217,000, and in California markets up to $228,000 for some levels. In Canada, the range is approximately CAD 153,000 to CAD 202,000. Compensation considers experience and market factors, and may include equity and benefits.

• Seniority level:
  Mid-Senior level
• Employme…