Data Scientist II: AI & ML Systems at Scale

Scribd; United States; Híbrido; USD 97 000 - 175 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Scribd Flex (flexible work model)

Health, dental, vision coverage

Mental health support

Paid time off

Parental leave

Retirement matching

Learning & development

Wellness stipend

Product access

Resumo da oferta

Scribd, Inc. is seeking a Data Scientist II to design and deploy high-impact ML models across content understanding tasks. You will work with ML engineers, data engineers and product teams to deliver end-to-end AI solutions at scale.

You will build models using massive data, explore NLP and generative approaches, and ensure robust performance with clear documentation and stakeholder communication. A collaborative, impact-driven culture awaits.

Qualificações

• 4+ years of post qualification experience in ML at scale and production.
• Strong Python proficiency and experience building ML pipelines.
• Experience with distributed data processing and model deployment.

Responsabilidades

• Develop and deploy ML models for content understanding and classification.
• Collaborate with data scientists, ML engineers and product partners.
• Design scalable AI systems and evaluate model performance at scale.
• Process large datasets with Python, SQL and Spark; document approaches clearly.
• Communicate results to stakeholders with concise technical writeups.
• Explore traditional NLP, LLMs and generative models to solve problems.

Conhecimentos

Python

Machine Learning

NLP

Distributed Systems

Spark

SQL

PyTorch

Big Data

Formação académica

Bachelor's or Master's in Statistics, Computer Science, Data Science, AI

Ferramentas

Spark

Databricks

PyTorch

Scikit-learn

Descrição da oferta de emprego

Scribd, Inc. is seeking a Data Scientist II to design and deploy high-impact ML models across content understanding tasks. You will work with ML engineers, data engineers and product teams to deliver end-to-end AI solutions at scale.

You will build models using massive data, explore NLP and generative approaches, and ensure robust performance with clear documentation and stakeholder communication. A collaborative, impact-driven culture awaits.