The Work
You will lead end-to-end delivery for software engineering AI training programs. The work includes turning research goals into clear workflows for coding datasets, repository tasks, agent workflows, reinforcement-learning environments, benchmarks, code review, and rubric-based evaluations.
You will improve quality, throughput, contributor performance, timelines, and cost across distributed programs. You will also work with research customers, report risks and quality trends, and mentor other program leads.
- Own program scope, timelines, quality, throughput, contributor performance, and cost.
- Design contributor workflows, review systems, capacity plans, quality controls, and reusable playbooks.
- Find bottlenecks and systematic dataset errors, then address their underlying causes.
- Build team-lead and reviewer systems for programs with 100 to 1,000 or more contributors.
- Turn research goals into task specifications and identify challenges that may not produce the intended signal.
- Use Python, SQL, or similar tools for quality sampling, defect analysis, throughput reporting, and operational reviews.
What It Takes
This is a contractor, part-time role open worldwide. The structured requirements list the role as entry level, while the work calls for strong technical judgment, program leadership, and the ability to review software engineering work.
- 20+ hours per week.
- Fluent in English.
- Experience leading complex programs involving multiple stakeholders in software engineering, technical program management, consulting, finance, startups, operations, or a similar setting.
- Strong analytical and problem-solving skills, including finding bottlenecks, defining useful metrics, and improving production performance.
- Experience managing distributed teams, contributor networks, marketplaces, or large-scale technical operations.
- Strong customer-facing communication skills, including managing expectations, communicating risks, and building client relationships.
- Ability to read and review code, understand test suites, and assess technical work independently in Python, TypeScript, Java, or Go.
- Helpful experience includes coding demonstrations, repository-level tasks, agent workflows, reinforcement-learning environments, benchmarks, code review, rubric-based evaluation, quality sampling, operational metrics, contributor management, or technical workflow design.
- Contractor and part-time engagement.
How It Works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI Training Work
AI training work is the human side of building artificial intelligence. People prepare and review examples such as code, model responses, and evaluations so AI systems can learn from useful, accurate feedback. OpenTrain helps people find these roles, build a profile, and apply in one place.