Remote | Senior Software Engineer — $50–$100/hour

24-Mag Llc; Northern, New York (KY, NY); Hybrid; USD 69,000 - 138,000; Part time

Job summary

24-MAG LLC is seeking experienced Senior Software Engineers for a remote, independent contractor engagement. You will contribute to reinforcement-learning environments and advanced AI-evaluation projects, with emphasis on Python3, Java, Rust, Go, C++, and TypeScript.

Responsibilities include building realistic AI evaluation environments, debugging, feature implementation, refactoring, and performance optimization, plus code reviews and technical documentation.

Qualifications

• Extensive professional software-engineering experience.
• Hands-on with Python3, Java, Rust, Go, C++, or TypeScript.
• Strong fundamentals in algorithms and data structures.
• Proven ability to debug complex systems and refactor large codebases.

Responsibilities

• Reinforcement-learning environment development for AI evaluation.
• Develop tasks involving debugging, feature development, refactoring, and optimisation.
• Build reproducible environments with golden reference solutions.
• Define problem statements, constraints and expected outcomes.
• Develop and document solution approaches and reasoning.
• Code review and technical validation of peer submissions.
• Produce technical documentation to support reproducibility.

Skills

Python3

Java

Rust

Go

C++

TypeScript

Algorithms

Debugging

Refactoring

Performance optimisation

Job description

We are sharing a specialised consulting opportunity for experienced Senior Software Engineers with strong expertise in Python3, Java, Rust, Go, C++, TypeScript, algorithms, debugging, feature development, codebase refactoring, and performance optimisation to contribute to an advanced AI training and software-engineering evaluation project.

Selected professionals will create reinforcement-learning environments that test advanced AI systems on realistic software-engineering problems involving bug fixing, feature implementation, refactoring, and performance optimisation. Each environment will require a reproducible technical setup together with a high-quality golden reference solution demonstrating the expected engineering approach. No prior experience in AI is required.

Key Responsibilities

Reinforcement Learning Environment Development

• Create realistic software-engineering environments for AI evaluation
• Design tasks involving debugging, feature development, refactoring, and optimisation
• Build reproducible environments that allow technical solutions to be evaluated consistently
• Define clear problem statements, constraints, and expected outcomes
• Develop golden reference solutions demonstrating correct engineering approaches

Software Development & Feature Implementation

• Contribute expert-level code across Python3, Java, Rust, Go, C++, or TypeScript
• Implement robust new functionality within existing codebases
• Apply sound software-engineering principles to real-world development scenarios
• Ensure new features are maintainable, scalable, and appropriately tested
• Evaluate trade-offs across different implementation approaches

Debugging & Defect Resolution

• Analyse complex software defects across varied codebases
• Identify root causes rather than applying superficial fixes
• Develop effective debugging strategies for difficult technical problems
• Resolve correctness, reliability, and integration issues
• Document reasoning behind technical diagnoses and fixes

Codebase Refactoring & Modernisation

• Refactor legacy or difficult-to-maintain code
• Improve structure, readability, modularity, and long-term maintainability
• Preserve required behaviour while improving implementation quality
• Identify unnecessary complexity and architectural weaknesses
• Apply modern software-engineering practices to existing systems

Performance Optimisation

• Identify performance bottlenecks across software systems
• Analyse algorithmic and implementation-level inefficiencies
• Improve runtime performance and resource usage where appropriate
• Validate that optimisations preserve correctness
• Explain technical trade-offs and performance impact clearly

Code Review & Technical Validation

• Review peer-contributed code and technical submissions
• Evaluate solutions for correctness, clarity, efficiency, and maintainability
• Identify hidden defects, unsupported assumptions, or incomplete reasoning
• Provide constructive technical feedback
• Validate that submissions satisfy task and environment requirements

Technical Documentation & Reasoning

• Document implementation decisions and solution approaches clearly
• Explain debugging, refactoring, and optimisation strategies
• Record technical assumptions and relevant trade-offs
• Produce documentation that supports reproducibility and evaluation
• Translate complex engineering reasoning into precise written explanations

Ideal Profile

• Significant professional software-engineering experience
• Strong hands-on expertise in at least one of Python3, Java, Rust, Go, C++, or TypeScript
• Deep understanding of algorithms and data structures
• Strong command of software-engineering fundamentals
• Proven ability to debug complex systems and resolve difficult defects
• Experience implementing substantial product or platform features
• Strong background in codebase refactoring and legacy-system modernisation
• Experience identifying and resolving performance bottlenecks
• Ability to reason across large and unfamiliar codebases
• Strong technical documentation and communication skills
• Experience taking high-impact features from concept through delivery is highly valuable
• Comfortable reviewing and validating other engineers' work
• Interest in AI and advanced technical evaluation is beneficial
• No prior AI-training experience is required

Engagement Details

• Independent contractor engagement
• Fully remote
• Expected commitment: approximately 15 hours per week
• Displayed compensation range: $50-$100/hour
• Actual compensation structure is output-based, with payment made per task that meets project specifications
• Task completion time may vary depending on individual experience and workflow
• Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
• Work will involve reinforcement-learning environment creation, software development, debugging, feature implementation, refactoring, performance optimisation, and technical validation
• Each task may require a reproducible environment and golden reference solution
• Roles are typically filled within approximately 48 hours
• Selected experts are expected to begin initial tasks within approximately 24-48 hours after onboarding
• Project scope, workload, technical domains, and evaluation standards may evolve depending on project requirements
• 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.

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