The role involves working as an open source contractor to create reinforcement learning environments that evaluate AI models' ability to solve complex software engineering workflows (e.g., DevOps, CI/CD, debugging) using common CLI tools. Contributors will produce production‑quality code, reviews, and documentation, design and optimize algorithms in languages such as C++, Python, Java, Go, TypeScript, or Rust, and collaborate with stakeholders to align deliverables with project goals.
Responsibilities
- Create reproducible RL environments that test a model's ability to solve complex software engineering workflows (DevOps/CI/CD/Debugging) using cli tools such as git, docker, gdb, asan, ffmpeg, along with a golden reference solution.
- Contribute production-quality code, reviews, and documentation to open-source repositories relevant to the customer’s project.
- Design, implement, and optimize complex algorithms and system components using one or more of the following languages: C++, Python, JAVA, GoLang, Typescript, or Rust.
- Identify and resolve technical challenges, bugs, and performance bottlenecks in existing codebases.
- Collaborate with other contributors and stakeholders to align deliverables with project goals and best practices.
- Create, maintain, and enhance technical documentation to support knowledge sharing and onboarding.
- Participate in code discussions and provide constructive feedback to elevate overall code quality.
Requirements
- Applicants must have clear open source contributions and profiles to showcase it like GitHub or GitLab.
Nice to have
- Previous experience working on large-scale, distributed codebases.
- Familiarity with modern AI or machine learning systems is a plus, though not required.
- Background in participating in rigorous code reviews and contributing to the development of software best practices.
Additional details
- Role Title: Open Source Contributor
- Role Type: Contractor
- Location: Remote
- micro1 is engaging with open source contributors to participate in a very complex and challenging Software Engineering project.
- Process:
- - Apply to the role, filling out the screening questions
- - Complete AI interview (approx. 30 minutes)
- - Technical Assessment (Tentative)
- - Hiring Manager review
- Compensation Structure: Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
- Start Timeline & Availability: We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
- Originally posted on Himalayas
Zobhira
