Computer Scientist for AI Model Training
Amazon.com, Inc.
Seattle, WA, United States
29 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$41,600.0 - $83,200.0
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Databases
Distributed Systems
Machine Learning
Information Technology
Job 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.
Requirements
- 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.
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