Remote | Research Engineer - Code Generation & Model Evaluation — $50–$100/hour

24-MAG; United States; Remote; USD 69,000 - 138,000; Part time

Benefits offered by this job

Remote work

Flexible hours

Contractor engagement

Job summary

24-MAG LLC is seeking experienced Research Engineers for a part-time, fully remote consulting role. You will work across multiple languages and codebases to debug issues, develop features, and evaluate AI-generated code for quality and performance.

Ideal candidates have strong problem-solving skills, open-source contributions, and the ability to communicate complex concepts clearly in a remote setting. This engagement is output-based with flexible hours and fast onboarding.

Qualifications

• Experience in competitive programming or problems analysis.
• Strong debugging and problem-solving abilities across codebases.
• Proficiency in software engineering fundamentals and modern languages.

Responsibilities

• Analyse, debug, and resolve issues across diverse codebases.
• Develop features and refactor code to improve quality and maintainability.
• Evaluate AI-generated code for correctness and performance.
• Provide clear technical feedback and documentation.

Skills

Competitive programming

Code analysis

Debugging

Software engineering

Open-source contributions

Multiple languages

Tools

Git

CI/CD

Job description

We are sharing a specialised part-time consulting opportunity for experienced Research Engineers with strong expertise in software engineering, competitive programming, code generation, debugging, and technical model evaluation to contribute to an advanced AI training and code-generation project.

Selected professionals will work across diverse codebases and programming languages to debug issues, implement and evaluate technical solutions, improve code quality, and develop realistic coding tasks used to assess advanced AI systems. The work combines hands-on software engineering with model evaluation, technical annotation, open-source collaboration, and rigorous code review. No prior experience in AI is required.

Key Responsibilities

Code Analysis, Debugging & Problem Solving

• Analyse, debug, and resolve technical issues across diverse software codebases
• Work with languages including Python3, Java, Rust, C , Go, TypeScript, or comparable technologies
• Investigate bugs, implementation failures, incorrect behaviour, and edge cases
• Apply strong algorithmic reasoning and data-structure knowledge to complex coding problems
• Evaluate multiple possible solution paths and select appropriate technical approaches

Feature Development & Codebase Improvement

• Contribute to the design and implementation of new features and technical enhancements
• Refactor existing codebases to improve maintainability, clarity, and adaptability
• Optimise code for performance, efficiency, and reliability
• Review implementation decisions and identify opportunities for architectural or technical improvement
• Produce high-quality, well-structured code that can be tested and evaluated consistently

Code Generation & Model Evaluation

• Develop and review realistic coding tasks used to evaluate AI model capabilities
• Assess AI-generated code for correctness, completeness, performance, and technical quality
• Identify logic errors, implementation weaknesses, constraint violations, and incomplete solutions
• Validate generated outputs against expected behaviour and objective technical requirements
• Help improve AI coding performance through rigorous technical assessment and feedback

Technical Feedback & Collaboration

• Author clear, actionable feedback and annotations supporting AI model training and evaluation
• Document technical decisions, best practices, implementation details, and problem-solving approaches
• Collaborate with technical stakeholders and open-source contributors to improve project quality
• Communicate complex engineering concepts clearly in written and verbal form
• Contribute to transparent knowledge-sharing and consistent technical standards across project workflows

Ideal Profile

• Strong expertise in competitive programming, coding problem analysis, or technically demanding software engineering
• Advanced proficiency in at least one of Python3, Java, Rust, C , Go, or TypeScript
• Solid understanding of algorithms, data structures, complexity, and software-engineering fundamentals
• Proven track record of open-source contributions or participation in collaborative software projects
• Strong analytical ability to interpret complex constraints and compare multiple technical solutions
• Experience with debugging, feature implementation, code refactoring, or performance optimisation
• Excellent written and verbal communication skills
• Ability to explain technical decisions and reasoning clearly and precisely
• Strong attention to detail in code validation, correctness, and output consistency
• Comfortable working independently within a remote and collaborative environment
• Ability to produce high-quality, well-documented work within demanding timelines
• No prior experience in AI research or model training is required

Engagement Details

• Part-time independent contractor engagement
• Fully remote
• Compensation: $50--$100/hour
• Compensation is output-based, with payment made for tasks that meet project specifications
• Minimum weekly submission requirements apply
• Work will involve debugging, feature implementation, codebase refactoring, performance optimisation, coding-task development, and AI model evaluation
• Selected professionals should be prepared to begin their first tasks within approximately 24--48 hours of completing onboarding
• Roles are typically filled within approximately 48 hours
• Project workload, task complexity, and completion time may vary depending on experience and workflow
• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.