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# Software Engineer Annotator

- **Company:** ODIX CONSULTING
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Computer Programming, Data Structures, Software Debugging, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Software Engineering, Large Language Models, Backend, Information Technology, Web Technologies
- **Published:** July 28, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p82k501ndr

## About the Role

* Bachelor's degree in computer science, software Engineering, or information Technology
 * Minimum of 3- 5 years' experience as a Software Engineer.
 * Prior experience in data annotation, AI training, and coding review.
 * Strong programming background in Python, Java, JavaScript, or C++, or Go.
 * Solid understanding of software engineering principles, data structures, and algorithms.
 * Ability to annotate, label, and evaluate code datasets accurately.
 * Familiarity with software development lifecycle (SDLC) and coding best practices.
 * Understanding of APIs, backend systems, and web technologies.
 * Basic knowledge of Artificial intelligence, machine learning, or Large Language Models (LLM) is an advantage.
 * Capability to compare multiple AI-generated responses and rank them based on accuracy and usefulness.
 * Familiarity with annotation platforms or labeling tools.

## Description

Job Summary: We are seeking an experienced Software Engineer Annotator responsible for evaluating, labeling, and improving software engineering datasets used for Artificial Intelligence and Large Language Model (LLM) training. The ideal candidate will apply strong programming knowledge to review AI-generated code, validate outputs, and ensure high-quality technical annotations aligned with engineering best practices., * Annotate and review software engineering datasets for AI training.

 * AI-generated code for correctness, efficiency, readability, and security.
 * Label datasets including code completion, debugging, refactoring, and optimization tasks.
 * Provide structured feedback to improve model performance.
 * Ensure adherence to annotation guidelines and quality standards.
 * Collaborate with AI trainers, reviewers, and data teams.


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