[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-ai-developer-jobs-in-brazil":3},{"Ques":4,"Slug":28,"Header":29,"job_category":96},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19,22,25],{"A":8,"Q":9},"These roles are explicitly marked Remote and are listed on Rex.zone for full-time remote work, while still targeting Brazil-focused hiring needs.","Are these AI Developer jobs in Brazil remote or onsite?",{"A":11,"Q":12},"Common work includes building ML services, deploying LLM features, creating model evaluation and prompt evaluation systems, and improving training data quality through data labeling and QA evaluation loops.","What kind of AI work is common for AI Developer jobs in Brazil?",{"A":14,"Q":15},"Many roles touch RLHF-adjacent workflows, such as integrating human feedback signals, preference-based evaluation, and safety constraints into LLM training pipelines and testing.","Do AI Developer roles involve RLHF?",{"A":17,"Q":18},"Both can be relevant. Listings often include NLP tasks like named entity recognition and text classification, and may also include computer vision pipelines supported by vision annotation and dataset QA.","Which domains are most relevant: NLP or computer vision?",{"A":20,"Q":21},"On Rex.zone, AI Developer roles may be offered by AI labs, tech startups, enterprises, BPOs, and annotation vendors building AI\u002FML products and LLM training pipelines.","What employer types hire for these roles?",{"A":23,"Q":24},"This page is optimized for FULL_TIME roles, but Rex.zone also commonly includes modifiers like contract, freelance, entry-level, and senior depending on the listing.","Is this page only for full-time roles?",{"A":26,"Q":27},"Highlight shipped production systems, measurable model performance improvement, MLOps practices, and your experience with evaluation tooling, prompt evaluation, and training data quality programs.","How should I tailor my application?","ai developer jobs in brazil",{"desc":30,"title":31,"content":32},"AI Developer jobs in Brazil on Rex.zone focus on building and deploying machine learning and large language model (LLM) systems end to end. You will design model training pipelines, implement prompt evaluation and RLHF-aligned workflows, improve training data quality with data labeling and QA evaluation signals, and ship production services for NLP and computer vision use cases. These Remote, FULL_TIME roles support AI labs, tech startups, and enterprise teams that need reliable model performance improvement, content safety labeling strategies, and scalable evaluation frameworks. Explore Rex.zone to find Brazil-focused AI developer openings, align your skills to the job requirements, and apply to roles that match your experience level and domain strengths.","AI Developer Jobs in Brazil",[33,50,58,67,76,83,89],{"h2":34,"desc":35},"AI Developer Jobs in Brazil — Remote (LinkedIn Job Metadata)",[36,37,38,39,40,41,42,43,44,45,46,47,48,49],"Title: AI Developer Jobs in Brazil","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: Python, Machine Learning, Deep Learning, LLMs, NLP, Computer Vision, MLOps, Model Evaluation, RLHF, Prompt Evaluation, Data Labeling, QA Evaluation","Salary Currency: USD","Salary Min: 63360","Salary Max: 126720","Pay Period: YEAR",{"h2":51,"desc":52},"About the Role",[53,54,55,56,57],"Build, fine-tune, and deploy ML and LLM-backed features for products serving users in Brazil and global markets, while collaborating remotely with distributed engineering teams.","Implement evaluation and monitoring to measure model quality, including prompt evaluation, QA evaluation, and offline\u002Fonline testing for model performance improvement.","Contribute to RLHF-adjacent workflows by integrating human feedback signals, preference data, and safety policies into training and evaluation loops.","Partner with data operations teams to define annotation guidelines compliance, improve training data quality, and resolve edge cases in data labeling and content safety labeling.","Develop and maintain model training pipelines, feature stores, experiment tracking, and CI\u002FCD for reliable model releases.",{"h2":59,"desc":60},"Key Responsibilities",[61,62,63,64,65,66],"Design and implement ML\u002FLLM services (APIs, batch jobs, streaming pipelines) with production reliability and measurable quality targets.","Create evaluation harnesses for LLM training pipelines, including rubric-based grading, pairwise preference testing, and regression suites for prompts.","Work across NLP and computer vision domains where applicable, including named entity recognition, document understanding, classification, and vision annotation feedback loops.","Develop data quality checks: sampling strategies, label audits, disagreement analysis, and golden-set validation to support QA evaluation.","Coordinate with stakeholders to translate product requirements into model objectives, datasets, and measurable acceptance criteria.","Document best practices for experimentation, prompt iteration, dataset versioning, and safe deployment.",{"h2":68,"desc":69},"Required Qualifications",[70,71,72,73,74,75],"Mid-Senior experience building and shipping ML systems in production.","Strong Python skills and hands-on experience with common ML frameworks and model serving patterns.","Practical knowledge of LLMs, prompt engineering, prompt evaluation, and model evaluation metrics.","Understanding of data labeling workflows, annotation guidelines, and training data quality considerations.","Experience with MLOps practices: experiment tracking, model registries, CI\u002FCD, monitoring, and rollback strategies.","Ability to communicate clearly in a remote environment and collaborate across engineering, product, and data teams.",{"h2":77,"desc":78},"Preferred Qualifications",[79,80,81,82],"Experience with RLHF concepts (preference data, reward modeling, policy tuning) and safety-focused evaluation.","Background in NLP (e.g., named entity recognition, retrieval, summarization) and\u002For computer vision pipelines.","Experience designing QA evaluation programs, building gold datasets, and performing error taxonomy analysis.","Familiarity with content safety labeling, policy development, and risk mitigation for user-facing AI features.",{"h2":84,"desc":85},"Work Model and Engagement",[86,87,88],"Remote: This role is explicitly Remote and supports distributed collaboration across time zones.","Employment Type: FULL_TIME.","Typical employer types on Rex.zone for this role include AI labs, tech startups, enterprises, BPOs, and annotation vendors supporting LLM training pipelines.",{"h2":90,"desc":91},"How to Apply on Rex.zone",[92,93,94,95],"Search and filter AI Developer jobs in Brazil on Rex.zone by domain (NLP, computer vision, content safety, LLM training).","Tailor your resume to highlight model training pipelines, evaluation frameworks, and shipped production outcomes.","Include examples of model performance improvement, training data quality initiatives, and prompt evaluation tooling you have built.","Apply directly to the listing that best matches your experience level and preferred tech stack.","Engineering"]