[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-remote-stem-jobs-brazil":3},{"Ques":4,"Slug":25,"Header":26,"job_category":62},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19,22],{"A":8,"Q":9},"Yes. This page targets remote STEM jobs in Brazil, designed for professionals working remotely while collaborating with distributed teams through Rex.zone.","Are these roles remote for candidates based in Brazil?",{"A":11,"Q":12},"Common work includes engineering support for AI\u002FML pipelines such as data labeling tooling, QA evaluation, prompt evaluation, named entity recognition validation, computer vision annotation review, content safety labeling checks, and RLHF feedback workflows tied to large language model evaluation.","What kind of STEM work is most common on Rex.zone for this posting?",{"A":14,"Q":15},"Yes. Employment Type is FULL_TIME and Remote Type is Remote, and the role is intended to remain explicitly remote.","Is this a full-time role and does it stay marked Remote?",{"A":17,"Q":18},"Emphasize STEM engineering fundamentals plus Python and SQL, training data quality, annotation guidelines compliance, QA evaluation, RLHF, prompt evaluation, named entity recognition, computer vision annotation, content safety labeling, and familiarity with LLM training pipelines.","What skills should I emphasize to match the job intent?",{"A":20,"Q":21},"Projects may support Technology teams across AI labs, tech startups, BPOs, and annotation vendors, depending on client demand and active programs on Rex.zone.","What industries and employer types might I work with?",{"A":23,"Q":24},"Across Rex.zone, roles can include contract, freelance, entry-level, and senior opportunities. This specific listing is configured as full-time remote with Mid-Senior experience level.","Do you offer contract, freelance, or different seniority levels?","remote stem jobs brazil",{"desc":27,"title":28,"content":29},"Remote STEM jobs in Brazil at Rex.zone focus on search-recognizable engineering roles that support AI\u002FML product delivery, LLM training pipelines, and evaluation workflows across NLP and computer vision. You will contribute to training data quality, annotation guidelines compliance, model performance improvement, and large language model evaluation through RLHF, data labeling, QA evaluation, prompt evaluation, and content safety labeling. These full-time remote roles align with real-world AI operations used by AI labs, tech startups, BPOs, and annotation vendors, while keeping clear deliverables, measurable quality targets, and production-grade engineering standards.","Remote STEM Jobs in Brazil",[30,32,35,38,41,44,47,50,53,56,59],{"h2":28,"desc":31},"Title: Remote STEM Engineer (Brazil)\nDate: 25-02-2026\nCompany: Rexzone\nCountry: US\nRemote Type: Remote\nEmployment Type: FULL_TIME\nExperience Level: Mid-Senior\nIndustry: Technology\nJob Function: Engineering\nSkills: STEM engineering, Python, SQL, data labeling, RLHF, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, content safety labeling, LLM training pipelines\nSalary Currency: USD\nSalary Min: 63360\nSalary Max: 126720\nPay Period: YEAR",{"h2":33,"desc":34},"About Rex.zone","Rex.zone is a platform that connects remote professionals with AI\u002FML and engineering work that strengthens model training pipelines, improves dataset reliability, and supports scalable evaluation operations. Teams commonly include engineers, data operations specialists, and quality-focused reviewers working with clear rubrics, sampling plans, and audit trails.",{"h2":36,"desc":37},"What You Will Do","You will deliver engineering outcomes that support AI training workflows and STEM production needs. Typical work includes building or improving tooling around data labeling, running QA evaluation checks, executing prompt evaluation tasks, validating named entity recognition outputs, supporting computer vision annotation review, monitoring training data quality, and contributing to model performance improvement through structured feedback loops such as RLHF.",{"h2":39,"desc":40},"Core Workflows You Will Support","You will operate within modern AI\u002FML delivery systems where quality and reproducibility matter. Common workflows include annotation guidelines compliance checks, dataset versioning support, evaluation set curation, error analysis for NLP and CV tasks, content safety labeling review, calibration sessions to reduce rater variance, and reporting metrics that map to large language model evaluation goals.",{"h2":42,"desc":43},"Required Qualifications","Mid-Senior engineering experience in a STEM domain, strong problem-solving and documentation habits, and comfort working remotely with distributed teams. You should be able to apply structured rubrics, follow annotation or evaluation instructions precisely, and use technical tools to validate outputs and improve process reliability.",{"h2":45,"desc":46},"Preferred Qualifications","Experience with AI data operations, RLHF or human feedback programs, QA evaluation methodologies, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. Familiarity with LLM training pipelines, dataset QA, sampling strategies, and precision\u002Frecall style metrics is helpful.",{"h2":48,"desc":49},"Tools and Technologies","Python and SQL for analysis and checks, spreadsheet-based QA workflows, issue tracking systems, internal annotation and evaluation tools, and basic scripting to automate routine validation. Depending on the project, you may work with NLP labeling interfaces, CV bounding box or segmentation tools, and safety taxonomy checklists.",{"h2":51,"desc":52},"Quality and Performance Expectations","You will be measured on training data quality, consistency against guidelines, audit-ready documentation, turnaround time, and the ability to surface ambiguous cases. Success means fewer rework cycles, clearer labeling instructions, improved inter-annotator agreement, and measurable model performance improvement signals tied to evaluation outcomes.",{"h2":54,"desc":55},"Who This Is For","These remote STEM jobs in Brazil are for engineers who want full-time remote work supporting AI product development and evaluation systems. Projects may be aligned with AI labs, tech startups, BPOs, and annotation vendors, and may span NLP, computer vision, and content safety programs.",{"h2":57,"desc":58},"How to Apply","Apply through Rex.zone with a resume that highlights engineering impact, remote collaboration, and any experience in data labeling, RLHF, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, content safety labeling, or LLM training pipelines. Include examples of documentation, QA process improvements, or tooling you built to improve reliability and throughput.",{"h2":60,"desc":61},"Employment Notes","Remote Type is Remote and Employment Type is FULL_TIME. Some projects may also be available as contract or freelance engagements depending on client needs, but this posting is for full-time remote roles. Opportunities may range from entry-level to senior across the platform; this listing targets Mid-Senior experience level.","Engineering"]