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# Computer Scientist for AI Model Training

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $41,600.0 - $83,200.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Databases, Distributed Systems, Machine Learning, Information Technology
- **Published:** July 13, 2026
- **Apply:** https://www.careerjet.com/job/register/us42ee89456da3ed7e8e71e673fbfbfbc9

## About the Role

* BSc, MSc, or PhD in Computer Science or a closely related discipline.
 * Experience in authoring technical papers, system design documents, or research publications.
 * Demonstrated expertise in specialized domains such as algorithms, distributed systems, networking, databases, or artificial intelligence.
 * Exceptional written and verbal communication skills, with a passion for precise and effective expression.
 * Proven ability to simplify complex concepts for diverse audiences and applications.
 * Track record of participation in collaborative research, technical reviews, or open-source contributions.
 * Adaptability and commitment to delivering high-quality contributions within project guidelines.

## Description

As a Computer Science Specialist, you will leverage your advanced expertise to support projects that train next-generation AI systems. Your contributions will directly influence how models learn, reason, and perform by providing high-quality, real-world input. This role is ideal for those with strong domain knowledge, as no prior experience in AI is required. Key Responsibilities

 * Analyze and evaluate computer science problems, solutions, and methodologies to inform AI system training.
 * Author, critique, or edit technical documentation, including system design documents and research papers, ensuring clarity and rigor.
 * Develop and review real-world computer science scenarios, datasets, and case studies for AI learning workflows.
 * Assess technical queries and propose detailed, well-structured responses based on best practices and foundational concepts.
 * Collaborate with project coordinators to refine task guidelines and optimize data quality.
 * Provide insightful written and verbal feedback to enhance model accuracy, relevance, and robustness.
 * Support the evaluation and continuous improvement of AI-driven tools through constructive analysis and domain expertise.


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