Scribd, Inc.
Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)
Scribd, Inc., New York, New York, us, 10261
About the Company
At Scribd, our mission is to spark human curiosity. We create a world of stories and knowledge, democratizing the exchange of ideas and information, and empowering collective expertise through our products: Everand, Scribd, Slideshare, and Fable.
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.
About the Role We are looking for a
Machine Learning Engineer
who will design, build, and optimize ML systems that scale to millions of users.
Key Responsibilities
Build large‑scale ingestion, transformation, and validation pipelines on Databricks; collaborate with engineering and analytics teams.
Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry‑standard frameworks.
Design and run A/B and N‑way experiments to measure the impact of model and feature changes.
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 professional ML or software engineering experience, delivering production ML systems at scale.
Proficiency in at least one key programming language (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 power recommendations, search, and next‑generation AI features used by millions of users worldwide.
Cutting‑edge projects: tackle challenging ML and AI problems, building novel generative features on Scribd’s massive and unique dataset.
Collaborative culture: a culture that values debate, fresh perspectives, and a willingness to learn from each other.
Flexible workplace: Scribd Flex offers autonomy in choosing daily work style while prioritizing in‑person collaboration.
Benefits, Perks, And Well‑Being
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short‑term/long‑term disability plans
401(k) / 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 (including 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: free access to best‑in‑class AI tools to boost productivity and accelerate innovation
Compensation Overview Base pay ranges depending on location:
San Francisco
$157,500–$230,000;
Other California
$129,500–$220,000;
Canada
$165,000 CAD–$218,000 CAD. Eligible for equity ownership and generous benefits.
Locations Primary residence must be in or near one of the following cities (including surrounding metro areas):
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
Equal Employment Opportunity 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.
Accessibility and Accommodations You can inform us of any reasonable adjustments to accommodate your needs at any point in the interview process by emailing accommodations@scribd.com.
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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.
About the Role We are looking for a
Machine Learning Engineer
who will design, build, and optimize ML systems that scale to millions of users.
Key Responsibilities
Build large‑scale ingestion, transformation, and validation pipelines on Databricks; collaborate with engineering and analytics teams.
Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry‑standard frameworks.
Design and run A/B and N‑way experiments to measure the impact of model and feature changes.
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 professional ML or software engineering experience, delivering production ML systems at scale.
Proficiency in at least one key programming language (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 power recommendations, search, and next‑generation AI features used by millions of users worldwide.
Cutting‑edge projects: tackle challenging ML and AI problems, building novel generative features on Scribd’s massive and unique dataset.
Collaborative culture: a culture that values debate, fresh perspectives, and a willingness to learn from each other.
Flexible workplace: Scribd Flex offers autonomy in choosing daily work style while prioritizing in‑person collaboration.
Benefits, Perks, And Well‑Being
Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short‑term/long‑term disability plans
401(k) / 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 (including 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: free access to best‑in‑class AI tools to boost productivity and accelerate innovation
Compensation Overview Base pay ranges depending on location:
San Francisco
$157,500–$230,000;
Other California
$129,500–$220,000;
Canada
$165,000 CAD–$218,000 CAD. Eligible for equity ownership and generous benefits.
Locations Primary residence must be in or near one of the following cities (including surrounding metro areas):
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
Equal Employment Opportunity 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.
Accessibility and Accommodations You can inform us of any reasonable adjustments to accommodate your needs at any point in the interview process by emailing accommodations@scribd.com.
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