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This fully remote, hourly paid contractor role is with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs. Your systems-level C expertise will directly help improve the world’s premier AI models used by millions of developers worldwide.
Key Responsibilities
- 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.
- Bachelor’s degree or higher in Computer Science, Electrical/Computer Engineering, or a closely related technical field.
- 4+ years of professional experience developing production software in C for systems, embedded, or performance-critical applications.
- Expert-level proficiency in C, including deep understanding of pointers, memory management, undefined behavior, and low-level debugging.
- Strong background in systems programming concepts such as concurrency, operating systems, hardware interaction, and performance optimization.
- Hands-on experience with build systems, compilers, linkers, and debugging tools commonly used in C development.
- Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines.
- Proven experience conducting detailed code reviews and enforcing coding standards for safety and maintainability in C codebases.
- Comfort working with version control, CI/CD workflows, and automated testing for C projects.
- Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
- Highly detail-oriented and systematic, with a methodical approach to evaluating reasoning quality and identifying subtle issues in low-level code.
Key Skills
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