Data Scientist II — ML/NLP at Scale (Flexible Work Model)

Apply; San Francisco (CA); On-site; USD 97,000 - 175,000; Full time

Benefits offered by this job

Flexible work model

Health coverage

Mental health support

Generous PTO

Parental leave

Retirement matching

Learning & development

Wellness stipend

Scribd product access

Enterprise AI tools

Job summary

Scribd, Inc. is seeking a Data Scientist II to design and deploy AI/ML systems using massive data scales. You will collaborate with ML Engineers, Data Engineers and Product teams to build end-to-end solutions with language models and traditional NLP methods.

The role emphasizes end-to-end visibility, simplicity in design, and delivering impact while working with large-scale data and cross-functional squads across content, search, translation and recommendations.

Qualifications

• 3+ years of post-qualification experience developing machine learning models and deploying to production.
• Proficiency in Python and building ML pipelines.
• Hands-on experience with distributed data processing frameworks (Spark/Databricks or similar).
• Experience with traditional NLP and generative models.
• SQL or PySpark experience.
• Bachelor's or Master's in quantitative field like Statistics/CS/Data Science/AI.

Responsibilities

• Focus on content classification use cases using NLP, LLMs and generative models.
• Investigate scalable solutions for challenging problems at Scribd.
• Collaborate with Data Scientists, ML Engineers and ML Data Engineers on cross-functional projects.
• Use algorithms ranging from Scikit-learn to PyTorch and third-party LLM APIs.
• Process large datasets with Python, SQL and Spark.
• Document approaches and results with clear written communications.

Skills

Python

NLP/ML

AI models

Data science

Education

Bachelor's or Master's in a quantitative field

Tools

Apache Spark

Databricks

Scikit-learn

NumPy

PyTorch

SQL

PySpark

Job description

Scribd, Inc. is seeking a Data Scientist II to design and deploy AI/ML systems using massive data scales. You will collaborate with ML Engineers, Data Engineers and Product teams to build end-to-end solutions with language models and traditional NLP methods.

The role emphasizes end-to-end visibility, simplicity in design, and delivering impact while working with large-scale data and cross-functional squads across content, search, translation and recommendations.