Lead QA for chemical-engineering AI training by reviewing technical content, mentoring reviewers, and enforcing safety-aware rubrics. Remote US contractor role, 20+ hrs/week, up to $105/hr with future opportunities through the expert network.
Generative AI & RLHF
Remote Hourly · $105/hr
$105/hr
Compensation
1 country
Eligibility
Expert
Experience
Jul 8, 2026
Posted
Open to applicants in
United States
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OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow careers teaching AI by aggregating specialized projects, consolidating work history, and supporting ongoing professional development.
OpenTrain AI is the hiring and contracting organization for this role. Contributors work remotely, build lasting freelance portfolios, and take part in projects that directly shape how modern AI systems behave.
About AI training work
AI training (data labeling / annotation / human feedback) is the human side of building AI: reviewers create, correct, and evaluate examples that train models. Many projects are text-based and involve rating responses, checking calculations, and enforcing domain-specific safety and accuracy standards.
This work is flexible and remote, making it a strong option for experienced professionals who want part-time, high-impact engagement with cutting-edge AI systems.
100% remote and flexible hours to fit your schedule.
Directly influence model behavior, safety, and factual accuracy.
Accessible career path with opportunities to mentor and lead contributors.
The role
As the Chemical Engineering Quality Assurance Lead you will review AI-generated chemical engineering content and trainer/QA submissions for technical accuracy, calculation quality, units consistency, safety, and rubric adherence.
You will provide precise written feedback, monitor quality trends, update guidelines, support onboarding, maintain documentation, and help keep remote contributors aligned on chemical-engineering-specific standards.
Focus: technical explanations, process calculations, mass/energy balances, reaction engineering, separations, process control, diagrams, and solution workflows.
Work type: text-based evaluation and rubric-driven ratings (label type: evaluation_rating).
What you'll do
You will perform hands-on QA of annotated content, coach reviewers, and maintain the quality infrastructure that keeps contributors producing reliable technical work.
Review engineering content and trainer/QA work for correctness and consistency.
Evaluate calculations, assumptions, units, and process logic against project rubrics.
Flag unsafe, misleading, or overconfident engineering recommendations.
Share updates, standards, and workflow changes with trainers and QAs.
Maintain style guides, FAQs, trackers, examples, honeypots, and onboarding materials.
Support onboarding and training calls for contributors.
Identify recurring issues and propose improvements to quality workflows.
Requirements
You must meet the core technical and communication requirements below to be effective in this lead role.
Degree in Chemical Engineering or a closely related engineering discipline.
3+ years of relevant chemical engineering, process, safety, review, or teaching experience.
Strong English communication skills for clear technical feedback.
Strong grasp of mass and energy balances, thermodynamics, fluid mechanics, heat transfer, mass transfer, reaction engineering, separation processes, process control, transport phenomena, and process design.
Experience evaluating technical work against detailed rubrics.
Familiarity with remote collaboration tools and preferably experience with Aspen Plus, Aspen HYSYS, MATLAB, Python, CHEMCAD, COMSOL, PFDs, P&IDs, Excel modeling, or process safety documentation.
Helpful background and who should apply
Ideal candidates have led or supported remote teams, are comfortable mentoring technical reviewers, and can translate deep engineering judgment into clear rubric-based feedback.
Experience leading or supporting remote teams of trainers, reviewers, technical writers, or QAs.
Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation is a plus.
Logistics, pay, and how it works
This is a remote contractor role with a United States hiring focus. The position is part-time (CONTRACTOR, PART_TIME) and expects roughly 20+ hours/week. There is no immediate project; OpenTrain will engage experts through its network as opportunities arise.
Compensation is pay-per-hour at up to $105/hour (USD). Work centers on text evaluations and rubric ratings; you will use remote collaboration tools and participate in onboarding and quality review meetings as needed.
Pay: up to $105/hour (USD).
Time: 20+ hours/week, remote contractor role.
Location: United States hiring focus; English required.
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