WFH.teamOpen app$104k-$208k
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What this posting tells you
Remote, project-based contractor role creating challenging software engineering tasks, reproducible environments, deterministic verifiers, and reference solutions for AI models. The listing states approximately 15 hours per week and pay of $50–100 per approved task, but does not specify the currency or clarify the exact pay basis beyond payment per approved task.
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Timezone overlap is not stated.
Not specified · Contractor
- Eligible hiring countries are not stated
- Required timezone overlap is not stated
Backend hiring on WFH.team
This role's listed pay is below the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.
Explore the remote job marketSoftware Engineer at micro1
Opportunity Snapshot
Pay: $50–100
Time per task: 5 hours for trainers and 1.5 hours for reviewers
Engagement: Project-based — paid per approved task
Commitment: ~15 hours per week
Location: Fully remote
You’ll need: Hands-on expertise in at least one of Python, Java, Rust, Go, C++, or TypeScript
Your tasks: Build challenging coding problems from real repositories, with reproducible environments and verifiers
Role Title: Software Engineer
Role Type: Contractor (~15 hrs a week)
Location: Remote
You’ll create Reinforcement Learning Environments that test a model’s ability to solve real software engineering problems: tracking down subtle bugs, building non-trivial features, refactoring, and optimizing performance. Each task means defining the problem, building a reproducible environment, and writing a reference solution.
Scope of Work
Create realistic, challenging coding tasks for frontier AI models, drawn from repositories you know well.
Design problems that require real engineering skill — subtle bugs, non-trivial features, meaningful performance work — not lookup or boilerplate.
Build a reproducible environment for each task.
Write deterministic verifiers that accept correct solutions across different valid implementations, while rejecting incorrect, incomplete, or hard-coded approaches.
Provide a reference solution showing how the task can be solved.
Flag tasks that turn out to be ambiguous or unverifiable rather than submitting them.
Preferred qualifications
Significant hands-on expertise in at least one of: 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.
Strong documentation and communication skills to articulate technical concepts clearly.
Interest in AI and its technical challenges — previous AI experience not required.
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required may vary depending on your experience and workflow.
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.
How the selection process works
Apply and complete the screening questions
Complete the AI interview for this role — it’s how your expertise gets in front of the client
Profile review
Onboarding — our Talent Ops team will get you set up
Working remotely at micro1
micro1 builds human-expertise data and evaluation infrastructure for AI models and agents. It recruits core-team employees and domain experts for AI training projects.
- Headquarters
- San Francisco Bay Area, California, United States
- Founded
- 2022
Expert opportunities are remote and can be flexible. International applicants are considered, subject to country exclusions and each project's requirements. Core-team work arrangements vary by opening; check the individual posting.
Apply through the official posting. Expert applicants complete an AI interview and skills certification, followed by project selection and onboarding. Certification does not guarantee a project or immediate work.