[Hiring] Software Engineer - Open Source Contributions @24-MAG

Role Description

We are sharing a specialised consulting opportunity for experienced Software Engineers with strong open-source development backgrounds and expertise in feature implementation, bug fixing, codebase refactoring, performance optimisation, algorithms, and multi-language software engineering to contribute to an advanced AI training and software-evaluation project. Selected professionals will work with established open-source codebases, implement and refine features, diagnose complex bugs, improve legacy systems, validate code quality, and develop technically rigorous solutions across multiple programming languages. The role is particularly suited to engineers with substantive hands-on open-source contributions and strong analytical problem-solving ability. No prior experience in AI is required.

Key Responsibilities

• Open-Source Feature Development
  • Develop and implement new features within established open-source repositories
  • Extend existing systems while respecting project architecture and contribution standards
  • Translate functional requirements into maintainable implementations
  • Integrate new functionality with existing modules and dependencies
  • Validate changes against expected project behaviour
• Bug Investigation & Resolution
  • Analyse complex software defects
  • Reproduce reported issues reliably
  • Trace execution and data flow to identify root causes
  • Develop robust fixes rather than surface-level workarounds
  • Validate corrections across relevant edge cases and regression scenarios
• Codebase Refactoring
  • Refactor legacy or difficult-to-maintain code
  • Improve code clarity, structure, and modularity
  • Reduce unnecessary complexity
  • Preserve expected behaviour while restructuring implementations
  • Align changes with established repository conventions
• Performance Optimisation
  • Identify performance bottlenecks
  • Analyse computational and architectural inefficiencies
  • Improve runtime or resource utilisation where appropriate
  • Compare alternative implementation strategies
  • Ensure optimisation work preserves correctness and maintainability
• Multi-Language Engineering
  • Work across codebases using Python, Java, Rust, C++, TypeScript, Go, C#, or related languages
  • Adapt quickly to language-specific ecosystems and tooling
  • Review equivalent implementations across different languages
  • Apply appropriate language conventions and engineering practices
  • Maintain technical consistency across multi-language projects
• Algorithms & Complex Problem Solving
  • Apply advanced algorithms and data structures to challenging technical problems
  • Analyse multifaceted constraints
  • Compare multiple solution pathways
  • Evaluate time and space complexity
  • Develop efficient and technically defensible implementations
• Code Validation & Quality Assurance
  • Review code for correctness and output consistency
  • Identify subtle implementation defects
  • Validate behaviour against project requirements
  • Assess maintainability and coding quality
  • Apply strong engineering standards throughout review workflows
• Technical Review & Peer Collaboration
  • Review proposed changes from other contributors
  • Evaluate implementation quality and architectural fit
  • Provide clear and actionable technical feedback
  • Collaborate remotely on issue resolution and feature development
  • Support consistent contribution standards across projects
• Technical Documentation
  • Produce concise technical write-ups
  • Explain solution design and implementation decisions
  • Document important architectural or algorithmic considerations
  • Communicate debugging findings clearly
  • Maintain useful project documentation where required
• AI Software Evaluation
  • Review AI-generated software solutions
  • Assess code for correctness, completeness, efficiency, and maintainability
  • Identify algorithmic or implementation weaknesses
  • Provide structured feedback supporting model improvement
  • Contribute real-world engineering judgement to AI-training workflows

Qualifications

• Expert-level proficiency in at least two of the following: Python, C++, Java, Rust, TypeScript, Go, or C#
• Extensive experience contributing to open-source software
• Demonstrated experience with feature development
• Strong bug-fixing and debugging ability
• Experience refactoring established codebases
• Strong performance-optimisation skills
• Strong understanding of algorithms and data structures
• Competitive-programming or advanced coding-problem experience is highly valuable
• Ability to analyse complex constraints and multiple possible solution approaches
• Strong code-review and validation skills
• Excellent attention to technical detail
• Strong written and verbal communication skills
• Ability to produce clear technical documentation
• Comfortable working independently in a remote collaborative environment
• Able to deliver well-documented, high-quality code under project deadlines
• No prior AI-training or model-evaluation experience is required

Engagement Details

• Independent contractor engagement
• Fully remote
• 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 open-source development, feature implementation, bug fixing, refactoring, performance optimisation, algorithms, code validation, and AI-generated software evaluation
• Strong hands-on open-source engineering experience is central to this engagement
• Relevant technologies may include Python, Java, Rust, C++, TypeScript, Go, C#, and related software ecosystems
• 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, repositories, languages, technical challenges, and evaluation standards may evolve depending on project requirements
• Work must be completed without using confidential or proprietary information belonging to any employer, client, private repository, software organisation, or other third party