Software Engineer Annotator

ODIX CONSULTING

United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

arc.dev

Tech stack

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

+4 more

Large Language Models Backend Information Technology Web Technologies

Job 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.

Requirements

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.