Online STEM Jobs in the United States

Rex.zone is hiring for online STEM jobs in the United States focused on software engineering, data engineering, and applied AI/ML workflows that power large language model training pipelines. In this remote, full-time role, you will build and maintain data systems, evaluation tooling, and automation that improve training data quality, annotation guidelines compliance, and model performance improvement. You will collaborate with cross-functional teams across NLP, computer vision, content safety labeling, and RLHF evaluation to support scalable data labeling, QA evaluation, prompt evaluation, and named entity recognition tasks. If you are seeking remote STEM work with clear impact on AI product quality, explore and apply on Rex.zone.

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Job Heading: Online STEM Jobs in the United States (Remote, Full-Time)

Title: Online STEM Engineer (Remote, United States) Date: 25-02-2026 Company: Rexzone Country: US Remote Type: Remote Employment Type: FULL_TIME Experience Level: Mid-Senior Industry: Technology Job Function: Engineering Skills: Software Engineering, Python, Data Engineering, SQL, Machine Learning, NLP, Computer Vision, LLM Evaluation, RLHF, Data Labeling QA Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR

About the Role

You will work remotely on STEM engineering initiatives that support AI/ML training and evaluation programs. Your work will connect production-grade engineering with annotation operations: building reliable pipelines for labeled datasets, implementing tooling for prompt evaluation and QA evaluation, and improving feedback loops used in RLHF. You will partner with data labeling and evaluation teams to operationalize annotation guidelines, measure inter-annotator agreement, and track training data quality to drive model performance improvement.

What You’ll Work On

You will design and maintain data workflows for NLP and computer vision annotation, including named entity recognition, content safety labeling, and multimodal labeling projects. You will build internal tools and dashboards that support audit trails, sampling plans, and quality metrics (e.g., precision/recall proxies, disagreement analysis). You will help standardize prompt evaluation rubrics, implement evaluator tooling, and enable scalable RLHF data collection and evaluation.

Responsibilities

Own end-to-end engineering delivery for remote STEM initiatives supporting LLM training pipelines. Build ETL/ELT jobs, data validation checks, and dataset versioning to ensure reproducibility. Implement QA evaluation workflows: gold sets, consensus methods, and review queues. Develop utilities for annotation guideline compliance checks and content policy enforcement in content safety labeling. Collaborate with AI labs, tech startups, and vendor partners to integrate labeling throughput, quality, and cost signals into planning.

Required Qualifications

Mid-Senior experience in software engineering or data engineering with production systems. Strong Python and SQL, with practical experience building reliable pipelines and automated tests. Familiarity with machine learning workflows, dataset curation, and ML evaluation concepts. Experience translating ambiguous requirements into measurable quality metrics and operational tooling. Ability to work asynchronously in a remote environment with clear written communication.

Preferred Qualifications

Experience supporting data labeling programs, annotation platforms, or BPO/annotation vendor integrations. Exposure to NLP tasks (e.g., named entity recognition) and LLM evaluation, including prompt evaluation and rubric-based scoring. Understanding of RLHF concepts, preference data collection, and evaluation sampling strategies. Familiarity with computer vision annotation formats and quality controls. Background in content safety labeling, policy enforcement, or trust & safety operations.

Employment Details

Remote, US-based. Full-time (FULL_TIME). This posting targets candidates seeking remote, full-time STEM work; additional modifiers candidates often search for include contract, freelance, entry-level, and senior—roles may vary across Rex.zone listings, but this opening is Remote and FULL_TIME as stated.

How to Apply

Apply through Rex.zone with a resume highlighting engineering ownership, production pipeline work, and any experience with LLM training data, data labeling QA, RLHF evaluation, NLP, computer vision annotation, or content safety labeling. Include examples of systems you built that improved training data quality, annotation guideline compliance, or model performance improvement.

Frequently Asked Questions

  • Q: Are these online STEM jobs in the United States fully remote?

    Yes. This role is marked Remote and is intended for US-based candidates working online.

  • Q: Is this position full-time or contract/freelance?

    This posting is FULL_TIME. Other Rex.zone listings may include contract or freelance roles, but this job is full-time.

  • Q: What STEM work will I do day to day?

    You will build and maintain engineering systems that support AI/ML workflows such as LLM training pipelines, data labeling QA, prompt evaluation, RLHF evaluation, and dataset quality measurement.

  • Q: Do I need prior AI/ML experience to apply?

    AI/ML experience is helpful, but the key requirement is strong engineering fundamentals. Experience with datasets, evaluation, NLP, computer vision annotation, or content safety labeling is a plus.

  • Q: What kinds of projects are included under evaluation and QA?

    Projects include QA evaluation workflows, rubric-based prompt evaluation, gold-set validation, disagreement analysis, annotation guideline compliance checks, and metrics that improve training data quality and model performance improvement.

  • Q: Where do I apply for this job?

    Apply via Rex.zone and search this page’s title/slug to find the active application path.

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