Job Details

Overview

Data Scientist II with experience developing and deploying machine learning models. You will help design and implement high impact AI and ML systems in cross-functional teams with Machine Learning Engineers, Data Engineers and Product. You will build models using large datasets, language models, and deploy models to production.

About The Company

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our products: Everand, Scribd, and Slideshare. We support a culture of boldness, customer focus, and deliberate collaboration. Scribd Flex enables flexible daily work styles in partnership with managers, with occasional in-person attendance to build collaboration and culture.

We hire for GRIT: goals, results, innovative ideas, and teamwork. GRIT guides our expectations for performance and collaboration.

Team and Role Context

The Applied Research team advances machine learning, natural language processing and generative AI to deliver value to users and the business. We collaborate with Product and Engineering to design and implement solutions across content enrichment, representation learning, recommendations, search, translation and more, at scale across text, image and audio.

Responsibilities

• Focus on content classification use cases, leveraging traditional NLP, LLMs and generative models
• Investigate scalable methods to solve challenging problems at Scribd
• Collaborate with Data Scientists, ML Engineers and ML Data Engineers on cross-functional projects
• Utilize algorithms from Scikit-learn, NumPy, PyTorch, and third-party LLM APIs
• Process large datasets with Python, SQL and Spark
• Communicate approaches and results to stakeholders, producing detailed, concise project documentation

Requirements

• 3+ years of post-qualification experience developing ML models, working with systems at scale, and deploying to production
• Proficiency in Python
• Hands-on experience building ML pipelines and working with distributed data processing frameworks (e.g., Apache Spark, Databricks)
• Intermediate level in at least three of: classification algorithms, NLP, search, information retrieval, named entity recognition, deep learning, generative models
• Intermediate level or greater experience with SQL or PySpark
• Bachelors or Masters in a relevant quantitative field

Compensation and Benefits

Base pay is part of total compensation and varies by location and level. Salary ranges shown reflect local benchmarks and geographic location. The roles may include equity, and a comprehensive benefits package. See the detailed ranges for the regions below.

• United States (California): $118,000 – $184,000
• United States (outside California): $97,000 – $175,000
• Canada: $123,000 CAD – $164,000 CAD

We consider experience, skills, education, and business needs in compensation decisions. This position is eligible for equity and benefits.

Working Location and Eligibility

Location eligibility requires primary residence in or near listed cities or within commuting distance as applicable by Scribd policy. Allowed locations include various U.S. cities, Canada (Ottawa, Toronto, Vancouver), and Mexico City, with in-person attendance as described in Scribd Flex.

Benefits, Perks, and Wellbeing

• Healthcare (Medical/Dental/Vision) covered for employees
• 12 weeks paid parental leave; disability plans
• 401k/RSP matching
• Stipends for home office, wellness, learning & development
• Annual vacation, personal days, holidays, sick time, and sabbaticals
• Free Scribd product subscriptions and employee resource groups
• AI tools access to boost productivity

Accessibility and equal opportunity: Scribd is an equal opportunity employer. We welcome applicants from diverse backgrounds and provide adjustments for accessibility as needed during the interview process. For accommodations, email ...@scribd.com.