Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)

Position Overview

At Scribd Inc. (pronounced “scribbed”), our mission is to spark human curiosity by democratizing the exchange of ideas and empowering collective expertise through our diverse suite of products including Everand, Scribd, Slideshare, and Fable. You’ll be joining a vibrant culture that prizes boldness, open debate, and balancing flexible work styles with purposeful in-person collaboration.

As part of the Recommendations team, you will power personalized discovery by combining large-scale data, cutting-edge machine learning, and product innovation. In this role as a Machine Learning Engineer, you will design, build, and optimize ML systems—from data ingestion through model training, deployment, and monitoring—that scale to millions of users. You will also help deliver next-generation AI features such as doc-chat and ask-AI, ensuring a fast, reliable, and cost-efficient pipeline.

Salary: In California, the range is approximately $146,500 to $228,000; outside of California in the US, between $120,000 and $217,000; and in Canada, between $153,000 CAD and $202,000 CAD. Your total compensation is determined based on local market benchmarks as well as factors like experience, job-related skill sets, and education.

Key Responsibilities

• 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 practical solutions.

Required Qualifications

• Experience Required: 4+ years of post-qualification 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 (e.g., Spark, Databricks, or similar).
• Strong cloud expertise (AWS, Azure, or GCP) and familiarity 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.
• Education: Bachelor’s or Master’s degree in Computer Science or equivalent professional experience.

Preferred Qualifications

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

Benefits & Perks

• 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 and accessories
• Learning & Development allowance and programs
• Quarterly stipend for wellness, WiFi, etc.
• Mental health support and resources
• Free subscription to the Scribd Inc. suite of products
• Referral bonuses
• Book benefit
• Sabbaticals
• Company-wide events and team engagement budgets
• Vacation and personal days, plus paid holidays (including winter break)
• Flexible sick time and volunteer day
• Access to employee resource groups and inclusivity programs
• Free access to best-in-class AI tools to boost productivity and streamline workflows