🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Remote STEM Jobs in the United States (Full-Time, Remote) Rex.zone connects 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 across distributed teams. 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. 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. Compensation Competitive hourly rate: $30–$50/hr (USD).
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.