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Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)
Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)Scribd, Inc. • San Francisco, CA, United States
Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)

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

Scribd, Inc. • San Francisco, CA, United States
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  • [job_card.full_time]
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About The Company

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 four products : Everand, Scribd, Slideshare, and Fable.

Our culture 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.

Flexible work 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.

What we look for 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 G oals, achieve R esults within their job responsibilities, contribute I nnovative ideas and solutions, and positively influence the broader T eam through collaboration and attitude.

About The Recommendations Team

The Recommendations 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. We :

  • Prototype 0→1 solutions in collaboration with product and engineering teams.
  • Build and maintain end‑to‑end, production‑grade ML systems for recommendations, search, and generative AI features.
  • Develop and operate services in Go, Python, and Ruby that power high‑traffic recommendation and personalization pipelines.
  • Run large‑scale A / B and multivariate experiments to validate models and feature improvements.
  • Transform Scribd’s massive, diverse dataset into actionable insights that drive measurable business impact.
  • Explore and implement generative AI for conversational recommendations, document understanding, and advanced search capabilities.

About The Role

We’re looking for a Machine Learning Engineer who will design, build, and optimize ML systems that scale to millions of users. 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. You’ll also play a key role in delivering next‑generation AI features like doc‑chat and ask‑AI that expand how users interact with Scribd’s content.

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 solutions that solve real user problems.
  • Requirements

    Must Have

  • 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 (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.
  • Expertise in experimentation design, causal inference, or ML evaluation methodologies.
  • Why Work With Us

  • 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 massive and unique dataset.
  • Collaborative Culture : Join a culture that values debate, fresh perspectives, and a willingness to learn from each other.
  • Flexible Workplace : Benefit from Scribd Flex, which offers autonomy in choosing your daily work style, while still prioritizing in‑person collaboration.
  • Compensation

    In the United States, salary ranges vary by geography. In California, the reasonable expected salary range is $157,500 to $230,000. Outside California, the range is $129,500 to $220,000. In Canada, the range is CAD 165,000 to CAD 218,000. Compensation decisions consider experience, skill set, education, and other factors. The salary range listed is for the level specified in the job scope. This position is also eligible for competitive equity ownership and a comprehensive benefits package.

    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

  • 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?

    / 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 accommodations@scribd.com 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.

    #J-18808-Ljbffr

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