Senior Machine Learning Engineer (Recommendations)

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 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 Goals achieve Results within their job responsibilities contribute Innovative ideas and solutions and positively influence the broader Team 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 01 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 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 the state of California the reasonably expected salary range is between $146500 minimum salary in our lowest geographic market within California to $228000 maximum salary in our highest geographic market within California.

In the United States outside of California the reasonably expected salary range is between $120000 minimum salary in our lowest US geographic market outside of California to $217000 maximum salary in our highest US geographic market outside of California.

In Canada the reasonably expected salary range is between $153000 CADminimum salary in our lowest geographic market to $202000 CADmaximum 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 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)

• 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 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 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.