Description review

GitHub Contributor

micro1 · Remote · back to the listing

HR standards

70/100

solid

Title ↔ description

25/100

poor

Reads as

Backend Engineer

88% confident

What this role officially is

software developer — ESCO, the EU occupation classification

Software developers implement or program all kinds of software systems based on specifications and designs by using programming languages, tools, and platforms.

Also known as: application developer, application programmer, solutions developer, programmer, software specialist, application software developer

How others title the same work

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What the listing never says

  • 17 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Role Title: GitHub Contributor

Role Type: Contractor (~15 hrs a week)

Location: Remote

micro1 is engaging expert Senior Software Engineers to support a customer’s innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

As an expert you will be creating Reinforcement Learning Environments which test and AI model's ability to solve complex software engineering problems related to fixing code, creating features, refactoring code and optimizing performance. You will be tasked with creating a reproducible environment and golden reference solution for the problem.

Applicants must have clear open source contributions and profiles to showcase it like GitHub or GitLab. (Preferably with C++, Python, JAVA, GoLang, Typescript, or Rust)

Scope of Work

• Contribute expert-level code samples, debugging strategies, and development insights in Python3, Java, Rust, Go, C++, or TypeScript.

• Analyze, troubleshoot, and resolve complex software defects and performance bottlenecks in diverse codebases.

• Implement robust new features, ensuring scalability, maintainability, and adherence to software best practices.

• Refactor and optimize legacy code to improve clarity, efficiency, and long-term reliability.

• Document technical reasoning, solution approaches, and code decisions to enhance AI training data quality.

• Review and validate peer-contributed code and technical submissions for accuracy and clarity.

Preferred Qualifications

• Significant hands-on expertise in at least one of the following: Python3, Java, Rust, Go, C++, or TypeScript.

• Deep understanding of algorithms, data structures, and software engineering principles.

• Proven ability to debug complex systems, resolve bugs, and deliver effective optimizations.

• Experience with large codebase refactoring and legacy system modernization.

• Track record of delivering high-impact features from conception through delivery within cross-functional projects.

• Strong documentation and communication skills to articulate technical concepts clearly.

• Interest in or curiosity about AI and its technical challenges (previous AI experience not required).

Process:

• Apply to the role, filling out the screening questions

• Complete AI interview (aprox. 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

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 78 before penalties). Reviewed 21 Sep 2026.