Implement scalable, maintainable features while following established software engineering practices.
Refactor existing code to improve readability, efficiency, maintainability, and reliability.
Apply algorithms, data structures, and computer science fundamentals to practical engineering problems.
Document technical reasoning, implementation decisions, debugging approaches, and solution strategies.
Review and validate code contributions and technical submissions for correctness, quality, and clarity.
Required Qualifications
Strong hands-on software engineering experience in at least one relevant programming language, such as Python, Java, Rust, Go, C++, or TypeScript.
Demonstrable software development experience, preferably supported by open-source contributions and a public GitHub profile.
Strong understanding of algorithms, data structures, and software engineering principles.
Practical experience debugging complex code, fixing bugs, and implementing features.
Familiarity with automated testing, code reviews, and software quality practices.
Ability to analyze unfamiliar codebases and develop effective, reliable solutions.
Strong analytical thinking, problem-solving, and technical communication skills.
Preferred Qualifications
Experience developing backend services, scalable applications, and APIs.
Significant contributions to open-source projects.
Experience refactoring large codebases or modernizing legacy systems.
Demonstrated success improving application performance and resolving system bottlenecks.
Experience delivering complex features from planning through implementation.
Familiarity with reproducible development environments, automated evaluation, or reinforcement learning environments.
Key Skills
Python 3, Java, Rust, Go, C++, TypeScript, Node.js, algorithms, data structures, GitHub, open-source development, codebase refactoring, bug fixing, feature implementation, performance optimization, automated testing, backend development, API development, debugging, code review, and logical reasoning.
Compensation
The hourly rate is $50–$100, equivalent to approximately $96,000–$192,000 per year at 1,920 working hours annually. This annualized figure is for comparison only.
Compensation is output-based: payment is tied to tasks that meet project specifications. Actual earnings depend on task availability, completion, acceptance, and time spent. Minimum submission requirements apply, including a minimum number of tasks per week.
Application and Assessment Process
Application: Submit your application and complete the screening questions.
AI Interview: Complete an interview of approximately 20 minutes.
Technical Assessment: Complete a coding assessment if your GitHub profile does not sufficiently demonstrate the required expertise. Candidates without suitable public contributions may be assessed through a technical platform.
Hiring Manager Review: Your experience, technical skills, and assessment results will be reviewed.
Candidates who complete the role-specific AI interview may progress through the process more quickly.
Start Timeline and Availability
The project seeks candidates who can begin promptly. Selected candidates should be prepared to start their first tasks within 24–48 hours of completing onboarding. Onboarding instructions will be provided after selection.
