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# Python Engineer (China or USA - Remote)

- **Company:** Brain Trust, LLC
- **Location:** Boston, MA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $83,200.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Code Review, Continuous Integration, Data Structures, Python (Programming Language), Performance Tuning, Software Engineering, Web Application Frameworks, Backend, Fastapi, Containerization, Information Technology, Codebase, Software Version Control
- **Published:** August 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=771454245af007d6

## About the Role

* Bachelor's degree or higher in Computer Science, Software Engineering, Mathematics, or a closely related technical field.
 * 7+ years of professional software engineering experience, with significant hands-on work in Python on production systems.
 * Deep knowledge of Python language features, the standard library, and common ecosystems such as web frameworks, data tooling, or backend services.
 * Strong understanding of algorithms, data structures, system design, and performance optimization in Python applications.
 * Proven experience designing, reviewing, and improving high-quality Python codebases, including code review and mentoring responsibilities.
 * Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines.
 * Comfort working with modern tooling such as version control systems, CI/CD pipelines, testing frameworks, and containerization technologies.
 * Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
 * Highly detail-oriented, with a structured and methodical approach to evaluating reasoning quality and identifying subtle errors in technical solutions.
 * Minimum C1 Chinese proficiency (written and spoken)

## Description

* Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
 * Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
 * Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.


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