Scribd
About The Company:
At Scribd, 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 nurture a culture where our employees can truly be themselves; where we engage in thoughtful debate and commitment, embracing plot twists, and where every employee is empowered to take action prioritizing the customer experience.
Our flexible work benefit, Scribd Flex, allows employees to choose the work-style that best suits their needs, while emphasizing intentional in-person collaboration to build connection and culture. Occasional in-person attendance is required for all employees.
At Scribd, we are inspired by GRIT - a blend of passion and perseverance toward long-term goals. We seek team members who can set and achieve
G oals, deliver
R esults, contribute
I nnovative ideas, and positively impact the broader
T eam through collaboration and attitude. About the Recommendations Team The Recommendations team drives personalized discovery across Scribd's products, offering relevant and engaging suggestions to millions. Our team combines frontend, backend, and ML engineers working hand-in-hand with product managers, data scientists, and analysts. We prototype exciting
0?1
solutions in collaboration with product and engineering teams. We build and maintain
end-to-end, production-grade ML systems
for recommendations, search, and generative AI features. We develop services using
Go, Python, and Ruby
that power high-traffic recommendation pipelines. We run A/B and multivariate experiments to validate models and feature enhancements. We transform Scribd’s
massive dataset
into actionable insights driving measurable business outcomes. We explore and implement
generative AI
for advanced user interactions. About the Role We seek a
Machine Learning Engineer
to design, build, and optimize ML systems that scale for millions of users. You will oversee the entire lifecycle, from data ingestion to model training, deployment, and monitoring, focusing on reliable and cost-effective pipelines. You'll also contribute to innovative AI features enhancing user interaction with Scribd content. Key Responsibilities: Data Pipelines:
Collaborate to build large-scale ingestion, transformation, and validation pipelines on
Databricks . Model Development & Deployment:
Train, evaluate, and deploy ML models to production using industry-standard frameworks. Experimentation:
Design and execute A/B experiments to measure impacts of model and feature updates. Cross-Functional Collaboration:
Work with product managers, data scientists, and analysts to identify opportunities and deliver solutions that address user needs. Requirements Must Have: 4+ years as an ML or software engineer with a solid track record in delivering production ML systems. Proficient in at least one major programming language (Python or Golang preferred; Scala or Ruby considered). Expertise in architecting large-scale ML pipelines and distributed systems. Deep familiarity with distributed data processing frameworks (Spark, Databricks, etc.). Strong cloud knowledge (AWS, Azure, or GCP) with experience in deployment platforms (ECS, EKS, Lambda). Proven ability to optimize performance and make informed design trade-offs. Experience leading technical projects and mentoring engineers. Bachelor's or Master's degree in Computer Science or equivalent experience. Nice to Have: Experience with embedding-based retrieval, large language models, and recommendation systems. Expertise in experimentation design or ML evaluation methodologies. Why Work With Us: High-Impact Environment:
Your work will include powering features used by millions worldwide. Innovative Projects:
Tackle challenging ML problems with a forward-thinking team using unique datasets. Collaborative Culture:
Join a team that welcomes diverse perspectives and values learning. Flexible Work Environment:
Enjoy autonomy in your work style while fostering in-person collaboration. At Scribd, we determine compensation based on local benchmarks and various factors. In California, the salary range is $146,500 to $228,000, and for the rest of the US, it ranges between $120,000 to $217,000. In Canada, the range is between $153,000 CAD to $202,000 CAD. We also offer competitive equity ownership and a comprehensive benefits package. Working at Scribd, Inc. Employees must reside near one of the following cities: 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., in the US; Ottawa, Toronto, Vancouver in Canada; Mexico City in Mexico. Benefits, Perks, and Wellbeing at Scribd: 100% Healthcare Insurance Coverage (Medical/Dental/Vision) for employees. 12 weeks paid parental leave. Short-term/long-term disability plans. 401k/RSP matching. Onboarding stipend for home office peripherals. Learning & Development allowance and programs. Quarterly stipend for wellness, WiFi, etc. Mental health support. Free subscription to Scribd’s suite of products. Referral bonuses. Book benefits. Sabbaticals. Company-wide events and team engagement budgets. Vacation & personal days, paid holidays, and flexible sick time. Volunteer day opportunities. Inclusive workplace with Employee Resource Groups. Access to AI tools to enhance productivity and innovation. Please note that benefits and perks may vary depending on your employment nature and geographical location. We aim to make our interview process accessible to everyone. If you need adjustments, please contact us. Scribd is an equal opportunity employer embracing diversity and committed to building a meaningful workplace.
G oals, deliver
R esults, contribute
I nnovative ideas, and positively impact the broader
T eam through collaboration and attitude. About the Recommendations Team The Recommendations team drives personalized discovery across Scribd's products, offering relevant and engaging suggestions to millions. Our team combines frontend, backend, and ML engineers working hand-in-hand with product managers, data scientists, and analysts. We prototype exciting
0?1
solutions in collaboration with product and engineering teams. We build and maintain
end-to-end, production-grade ML systems
for recommendations, search, and generative AI features. We develop services using
Go, Python, and Ruby
that power high-traffic recommendation pipelines. We run A/B and multivariate experiments to validate models and feature enhancements. We transform Scribd’s
massive dataset
into actionable insights driving measurable business outcomes. We explore and implement
generative AI
for advanced user interactions. About the Role We seek a
Machine Learning Engineer
to design, build, and optimize ML systems that scale for millions of users. You will oversee the entire lifecycle, from data ingestion to model training, deployment, and monitoring, focusing on reliable and cost-effective pipelines. You'll also contribute to innovative AI features enhancing user interaction with Scribd content. Key Responsibilities: Data Pipelines:
Collaborate to build large-scale ingestion, transformation, and validation pipelines on
Databricks . Model Development & Deployment:
Train, evaluate, and deploy ML models to production using industry-standard frameworks. Experimentation:
Design and execute A/B experiments to measure impacts of model and feature updates. Cross-Functional Collaboration:
Work with product managers, data scientists, and analysts to identify opportunities and deliver solutions that address user needs. Requirements Must Have: 4+ years as an ML or software engineer with a solid track record in delivering production ML systems. Proficient in at least one major programming language (Python or Golang preferred; Scala or Ruby considered). Expertise in architecting large-scale ML pipelines and distributed systems. Deep familiarity with distributed data processing frameworks (Spark, Databricks, etc.). Strong cloud knowledge (AWS, Azure, or GCP) with experience in deployment platforms (ECS, EKS, Lambda). Proven ability to optimize performance and make informed design trade-offs. Experience leading technical projects and mentoring engineers. Bachelor's or Master's degree in Computer Science or equivalent experience. Nice to Have: Experience with embedding-based retrieval, large language models, and recommendation systems. Expertise in experimentation design or ML evaluation methodologies. Why Work With Us: High-Impact Environment:
Your work will include powering features used by millions worldwide. Innovative Projects:
Tackle challenging ML problems with a forward-thinking team using unique datasets. Collaborative Culture:
Join a team that welcomes diverse perspectives and values learning. Flexible Work Environment:
Enjoy autonomy in your work style while fostering in-person collaboration. At Scribd, we determine compensation based on local benchmarks and various factors. In California, the salary range is $146,500 to $228,000, and for the rest of the US, it ranges between $120,000 to $217,000. In Canada, the range is between $153,000 CAD to $202,000 CAD. We also offer competitive equity ownership and a comprehensive benefits package. Working at Scribd, Inc. Employees must reside near one of the following cities: 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., in the US; Ottawa, Toronto, Vancouver in Canada; Mexico City in Mexico. Benefits, Perks, and Wellbeing at Scribd: 100% Healthcare Insurance Coverage (Medical/Dental/Vision) for employees. 12 weeks paid parental leave. Short-term/long-term disability plans. 401k/RSP matching. Onboarding stipend for home office peripherals. Learning & Development allowance and programs. Quarterly stipend for wellness, WiFi, etc. Mental health support. Free subscription to Scribd’s suite of products. Referral bonuses. Book benefits. Sabbaticals. Company-wide events and team engagement budgets. Vacation & personal days, paid holidays, and flexible sick time. Volunteer day opportunities. Inclusive workplace with Employee Resource Groups. Access to AI tools to enhance productivity and innovation. Please note that benefits and perks may vary depending on your employment nature and geographical location. We aim to make our interview process accessible to everyone. If you need adjustments, please contact us. Scribd is an equal opportunity employer embracing diversity and committed to building a meaningful workplace.