Senior Code Reviewer for LLM Data Training (TypeScript) - SME Work , remote - Indonesia

Senior Code Reviewer for LLM Data Training (TypeScript) - SME Work , remote - Indonesia

deadline of application is on Jul, 08 from  https://www.linkedin.com/jobs/

Job Responsibility /Description:

  • This latest job opening is open to job seekers who have the latest education / graduate. Job Vacancies in this Senior Code Reviewer for LLM Data Training (TypeScript) field have been opened and published up to the specified time.
  • Review and audit annotator evaluations of AI-generated TypeScript code.
  • Assess if the TypeScript code follows the prompt instructions, is functionally correct, and secure.
  • Validate code snippets using proof-of-work methodology.
  • Identify inaccuracies in annotator ratings or explanations.
  • Provide constructive feedback to maintain high annotation standards.
  • Work within Project Atlas guidelines for evaluation integrity and consistency.

Job Requirement / Minimum Qualification:

  • Please attach your last CV. Only shortlist candidate will be contacted.
  • 5–7+ years of experience in TypeScript development, QA, or code review.
  • Strong knowledge of TypeScript syntax, debugging, edge cases, and testing.
  • Comfortable using code execution environments and testing tools.
  • Excellent written communication and documentation skills.
  • Experience working with structured QA or annotation workflows.
  • English proficiency at B2, C1, C2, or Native level.
  • Preferred Qualifications
  • Experience in AI training, LLM evaluation, or model alignment.
  • Familiarity with annotation platforms.
  • Exposure to RLHF (Reinforcement Learning from Human Feedback) pipelines.
Other Position
 Jobs Summary
JOB LEVEL
Experienced,Expertised,Excellent,
JOB CATEGORY
IT Related Services,Software,rtificial Intelligence

About SME Work

SME is a platform that bridges subject-matter experts with AI projects, enabling them to contribute their knowledge to improve AI models. It offers flexible opportunities to work on tasks like data labeling, quality assurance, and domain-specific problem-solving while earning competitive pay.

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