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

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 three products : Everand, Scribd, and Slideshare.

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.

When it comes to workplace structure, we believe in balancing individual flexibility and community connections. Its 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.

So what are we looking for in new team members? Well, 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. Heres what that means for you : were 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 Scribds 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 Scribds 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

Were looking for a Machine Learning Engineer who will design, build, and optimize ML systems that scale to millions of users. Youll 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. Youll also play a key role in delivering next-generation AI features like doc-chat and ask-AI that expand how users interact with Scribds 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 Scribds 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.

Bachelors or Masters 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 Scribds 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.

At Scribd, 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 $146,500 [minimum salary in our lowest geographic market within California] to $228,000 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $120,000 [minimum salary in our lowest US geographic market outside of California] to $217,000 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $153,000 CAD[minimum salary in our lowest geographic market] to $202,000 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.

Working at Scribd, inc.

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

• Benefits / perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work.

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)