STEM Careers in the United States

STEM careers in the United States at Rex.zone focus on building and evaluating real AI/ML systems—especially large language model workflows where engineers translate product goals into training data quality, RLHF evaluation, prompt evaluation, and QA signals that improve model performance. This remote, full-time role connects day-to-day engineering with LLM training pipelines, data labeling operations, annotation guidelines compliance, and content safety labeling. You will collaborate with cross-functional teams to define evaluation criteria, debug failure modes, and ship reliable tooling that supports NLP and computer vision annotation at scale, while maintaining measurable quality and privacy standards across datasets and model iterations.

STEM Careers in the United States

About the Role

You will work remotely on Rex.zone to support STEM-aligned engineering initiatives that improve AI system reliability. The role centers on designing, implementing, and maintaining workflows for LLM training pipelines, including RLHF evaluation, prompt evaluation, QA evaluation, and training data quality checks. You will partner with data operations and product teams to translate requirements into measurable labeling specs, evaluation rubrics, and automated quality controls across NLP, named entity recognition, computer vision annotation, and content safety labeling.

What You Will Do

You will: build and improve evaluation tooling for large language model evaluation; define and maintain annotation guidelines compliance checks; design sampling strategies and acceptance criteria for training data quality; analyze error patterns and propose fixes that drive model performance improvement; collaborate with data labeling teams and vendors to resolve ambiguity and reduce rework; implement QA evaluation dashboards and metrics (inter-annotator agreement, precision/recall proxies, drift checks); support prompt evaluation experiments and feedback loops for RLHF; help enforce privacy, security, and policy constraints for sensitive data.

Required Qualifications

You have: mid-senior experience in a STEM field (engineering, computer science, data science, or related); strong programming fundamentals and ability to ship production-quality tools; familiarity with machine learning concepts and LLM evaluation methods; experience with data labeling, QA evaluation, or dataset curation for NLP and/or computer vision; ability to write clear specs, rubrics, and annotation guidelines; strong analytical skills for debugging dataset and evaluation issues; comfort working cross-functionally in remote teams.

Preferred Qualifications

Nice to have: experience with RLHF or preference modeling workflows; hands-on work with prompt evaluation and rubric-based scoring; knowledge of named entity recognition, taxonomy design, and ontology management; experience with content safety labeling and policy enforcement; exposure to annotation vendor management or BPO operations; familiarity with evaluation metrics, calibration, and inter-annotator agreement; experience supporting AI labs, tech startups, or annotation vendors.

Tools and Workflows You Will Use

You will use engineering and evaluation workflows aligned to AI/ML training: dataset versioning and audit trails; automated validation for annotation guidelines compliance; QA evaluation pipelines; human-in-the-loop review loops; prompt evaluation harnesses; sampling and stratification for training data quality; error analysis for model performance improvement; operational reporting for throughput, rework, and quality.

Remote Work and Employment Details

This is a Remote, FULL_TIME role in the United States. You will collaborate asynchronously with distributed stakeholders and maintain clear documentation, reproducible experiments, and measurable QA evaluation outcomes. Contract, freelance, entry-level, and senior openings may exist on Rex.zone, but this posting is specifically for a remote full-time mid-senior role.

How to Apply on Rex.zone

Explore and apply through Rex.zone by submitting your resume and a brief summary of relevant STEM engineering work, especially any experience with LLM evaluation, RLHF, data labeling, prompt evaluation, QA evaluation, NLP, computer vision annotation, named entity recognition, or content safety labeling. Highlight examples where you improved training data quality or delivered model performance improvement through better evaluation design.

Frequently Asked Questions

Q: What does “STEM careers in the United States” mean for this role?
It refers to a STEM-aligned engineering position based in the US that supports AI/ML development on Rex.zone, with a focus on LLM training pipelines, evaluation, and data quality systems.
Q: Is this job remote and full-time?
Yes. The role is Remote and FULL_TIME, aligned to US-based hiring for Rexzone.
Q: What are the core workflows I will work on?
You will work on large language model evaluation, RLHF evaluation loops, prompt evaluation, QA evaluation, training data quality controls, and annotation guidelines compliance across NLP and computer vision annotation.
Q: Do I need prior RLHF experience?
It is helpful but not required. Strong experience in evaluation design, data labeling/QA, and ML/LLM concepts can be sufficient to ramp into RLHF workflows.
Q: What types of employers does this experience translate to?
The skills map to AI labs, tech startups, enterprise ML teams, BPOs, and annotation vendors that run large-scale labeling, evaluation, and content safety programs.
Q: What salary range is listed for this role?
The posted range is 63360 to 126720 USD per year, depending on experience and role fit.

230+Domains Covered

120K+PhD, Specialist, Experts Onboarded

50+Countries Represented

Industry-Leading Compensation

We believe exceptional intelligence deserves exceptional pay. Our platform consistently offers rates above the industry average, rewarding experts for their true value and real impact on frontier AI. Here, your expertise isn't just appreciated—it's properly compensated.

Work Remotely, Work Freely

No office. No commute. No constraints. Our fully remote workflow gives experts complete flexibility to work at their own pace, from any country, any time zone. You focus on meaningful tasks—we handle the rest.

Respect at the Core of Everything

AI trainers are the heart of our company. We treat every expert with trust, humanity, and genuine appreciation. From personalized support to transparent communication, we build long-term relationships rooted in respect and care.

Ready to Shape the Future of Engineering?

Apply Now.