Remote STEM Jobs in the United States

Remote STEM jobs in the United States at Rex.zone connect engineers and STEM professionals to real AI/ML production workflows, including LLM training pipelines, RLHF evaluation, data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. You will support training data quality, annotation guidelines compliance, and model performance improvement for enterprise and research teams across NLP, CV, and multimodal systems—while staying fully remote. Explore full-time opportunities designed for Mid-Senior candidates working with modern tooling, measurable quality metrics, and clear delivery expectations across distributed teams.

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Remote STEM Jobs in the United States (Full-Time, Remote)

Title: Remote STEM Engineer (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: STEM engineering, Python, data analysis, machine learning, statistics, SQL, experiment design, cloud computing, MLOps Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR

About the Role

As a Remote STEM Engineer (United States), you will deliver measurable outcomes across applied engineering and AI/ML support workstreams. Your day-to-day may include building and validating data pipelines, improving training data quality, running statistical analyses, and partnering with ML teams on evaluation harnesses. You will also contribute to LLM training pipelines through RLHF tasks such as prompt evaluation and QA evaluation, and help define annotation guidelines compliance for data labeling programs (NER, computer vision annotation, and content safety labeling). This role is aligned with remote, full-time delivery and supports employer types ranging from AI labs and tech startups to annotation vendors and BPO partners on Rex.zone.

Key Responsibilities

["Design, implement, and maintain data workflows that support machine learning and large language model evaluation.","Execute RLHF-related processes including prompt evaluation, preference ranking, and rubric-based QA evaluation.","Define and operationalize annotation guidelines compliance to improve training data quality and reduce label noise.","Perform named entity recognition (NER) and schema validation checks; troubleshoot edge cases and ambiguous labeling.","Support computer vision annotation programs (bounding boxes, polygons, keypoints) and audit inter-annotator agreement.","Contribute to content safety labeling and policy-driven evaluation for harmful, sensitive, and restricted content.","Create metrics and dashboards for model performance improvement (accuracy, precision/recall, calibration, and error taxonomy).","Collaborate asynchronously with distributed teams; document decisions, experiments, and release notes."]

Required Qualifications

["Bachelor’s degree (or higher) in a STEM field (CS, EE, Math, Stats, Physics, or related).","Mid-Senior experience delivering engineering or applied data/ML work in production or research-adjacent environments.","Proficiency with Python and common data tooling (pandas, NumPy) plus SQL for analysis and reporting.","Understanding of ML evaluation concepts: ground truth construction, bias/variance, and dataset shift.","Experience with quality assurance practices: sampling plans, audit checklists, and root-cause analysis.","Ability to write clear documentation and follow structured rubrics for QA evaluation and labeling tasks.","Comfort working fully remote with time-zone coordination across the United States."]

Preferred Qualifications

["Exposure to NLP and LLM workflows (prompting, prompt evaluation, instruction tuning concepts).","Experience with RLHF or human-in-the-loop evaluation pipelines.","Computer vision annotation familiarity and tooling experience (CVAT, Labelbox, or similar).","Knowledge of content safety labeling standards and policy frameworks.","Experience with cloud platforms (AWS/GCP/Azure) and CI/CD or MLOps basics.","Hands-on experience improving annotation guidelines compliance and inter-annotator agreement."]

Work Modifiers and Role Fit

["Remote: This role is explicitly remote within the United States.","Full-time: FULL_TIME employment type.","Contract/Freelance: Not the default for this posting, but Rex.zone may feature contract and freelance STEM roles.","Entry-level/Senior: This posting targets Mid-Senior; Rex.zone also lists entry-level and senior variants.","Domains: NLP, computer vision, LLM training pipelines, RLHF, content safety.","Employer types: AI labs, tech startups, annotation vendors, BPO teams."]

How to Apply on Rex.zone

["Search Rex.zone for ‘remote STEM jobs united states’ and open the matching listing.","Review required skills and confirm Remote, FULL_TIME alignment.","Submit your application with a resume highlighting engineering delivery, data analysis, and ML evaluation experience.","If applicable, include examples of QA evaluation, data labeling oversight, or RLHF/prompt evaluation work."]

Frequently Asked Questions

  • Q: What does a Remote STEM job in the United States mean on Rex.zone?

    It refers to STEM roles that can be performed fully Remote while located in the US, often supporting engineering delivery plus AI/ML workflows such as LLM training pipelines, RLHF evaluation, and training data quality initiatives.

  • Q: Is this role full-time and remote?

    Yes. The role is marked Remote and FULL_TIME, intended for Mid-Senior candidates based in the United States.

  • Q: What kinds of AI/ML tasks are common in these remote STEM roles?

    Common tasks include QA evaluation, prompt evaluation, RLHF-style preference work, data labeling program support, named entity recognition validation, computer vision annotation auditing, and content safety labeling—focused on model performance improvement and annotation guidelines compliance.

  • Q: Do I need prior RLHF experience?

    It is preferred but not strictly required. Strong fundamentals in data analysis, experimentation, and quality assurance can transfer well to RLHF evaluation and LLM evaluation workflows.

  • Q: What skills should I highlight to match remote STEM jobs in the United States?

    Highlight Python, SQL, data analysis, statistics, experiment design, cloud computing, and ML evaluation. If you have it, add experience with LLM training pipelines, RLHF, data labeling, NER, computer vision annotation, and content safety labeling.

  • Q: What employer types post remote STEM roles on Rex.zone?

    You may see roles from AI labs, tech startups, enterprise technology teams, annotation vendors, and BPO organizations supporting AI training and evaluation operations.

  • Q: Are contract or freelance options available too?

    This posting is FULL_TIME, but Rex.zone also includes contract and freelance remote STEM roles depending on current listings and project needs.

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