[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-entry-level-coding-jobs-remote":3},{"Slug":4,"Header":5,"Ques":33,"job_category":66},"entry level coding jobs remote",{"desc":6,"title":7,"content":8},"Entry-level coding jobs (remote) at Rex.zone connect junior developers and data labeling associates to real AI\u002FML training workflows. These roles span Python scripting, QA evaluation, prompt evaluation, RLHF contributions, named entity recognition, computer vision annotation, content safety labeling, and LLM training pipelines. The intent is to hire remote candidates who improve training data quality, maintain annotation guidelines compliance, and enable model performance improvement through large language model evaluation and simple automation. Candidates learn modern tooling, version control, and cloud-integrated pipelines while contributing to production datasets and evaluation suites. Explore openings, compare employers, and apply on Rex.zone to start a remote career in coding, data operations, and model evaluation.","Entry-Level Coding Jobs (Remote)",[9,12,15,18,21,24,27,30],{"h2":10,"desc":11},"About the Role","This entity covers junior developer and data operations roles supporting AI labs, tech startups, BPOs, and annotation vendors. Typical tasks include writing small Python or JavaScript utilities, preparing datasets, running evaluation scripts, handling prompt evaluation for LLMs, and assisting RLHF workflows. Work may include named entity recognition, computer vision annotation, content safety labeling, synthetic data generation, and validation.",{"h2":13,"desc":14},"Key Responsibilities","Implement simple scripts and unit tests; follow annotation guidelines compliance; run dataset checks for training data quality; participate in model performance improvement via large language model evaluation; prepare prompts and evaluation rubrics; triage issues; document workflows; collaborate asynchronously with engineers, QA, and data labeling teams; uphold privacy and content safety standards.",{"h2":16,"desc":17},"Required Skills","Foundational coding in Python or JavaScript; Git and GitHub; JSON, CSV, and REST APIs; basic SQL; comfort with Linux, CLI, and Jupyter; attention to detail for data labeling; clear written communication; ability to follow SOPs; familiarity with Label Studio or similar tools; eagerness to learn RLHF, evaluation pipelines, and cloud-based workflows.",{"h2":19,"desc":20},"Workflows & Tools","LLM training pipelines, RLHF data collection, prompt evaluation frameworks, annotation portals (Label Studio, CVAT), QA dashboards, VS Code, Jupyter, Docker, issue trackers, CI\u002FCD, and cloud services (AWS, GCP, Azure). Candidates collaborate via async tools, maintain reproducible experiments, and submit PRs aligned with coding standards.",{"h2":22,"desc":23},"Employment Types & Domains","Remote, contract, freelance, full-time, part-time, internship, entry-level, junior, and senior tracks. Domain coverage includes NLP, computer vision, content safety, and LLM training. Employers range from AI labs and tech startups to BPOs and specialized annotation vendors.",{"h2":25,"desc":26},"Compensation & Career Growth","Compensation varies by employer, region, and skill depth; packages include hourly and monthly arrangements for remote contract, freelance, and full-time roles. Growth paths lead from junior coder or annotator to QA lead, data engineer, model evaluation specialist, or MLOps contributor with mentorship and upskilling.",{"h2":28,"desc":29},"How to Apply on Rex.zone","Create your profile, upload a concise resume, add GitHub links and sample notebooks, and set filters for remote and entry-level. Browse curated listings, compare employers, and apply directly on Rex.zone. Track applications, complete coding or annotation assessments, and receive interview invitations.",{"h2":31,"desc":32},"Location & Time Zones","Fully remote roles across Americas, EMEA, and APAC. Teams typically coordinate in UTC-friendly windows; most work is asynchronous with flexible schedules, provided deadlines and quality standards are met.",{"title":34,"content":35},"Frequently Asked Questions",[36,39,42,45,48,51,54,57,60,63],{"A":37,"Q":38},"It is a junior role focused on data operations and simple engineering tasks that support AI\u002FML workflows. Typical duties include Python scripting, dataset preparation, prompt evaluation, RLHF data collection, named entity recognition, computer vision annotation, content safety labeling, and large language model evaluation.","What is an entry-level coding job in AI\u002FML?",{"A":40,"Q":41},"Yes. Positions on Rex.zone are designed for remote work with asynchronous collaboration. Teams may request overlapping hours for standups, code reviews, and evaluation cycles, but flexibility is standard.","Is this role fully remote?",{"A":43,"Q":44},"Basic proficiency in Python or JavaScript, Git, JSON\u002FCSV handling, REST APIs, simple SQL, Linux shell, and careful attention to annotation guidelines. Clear communication and the ability to follow SOPs are essential.","Which skills help me get hired quickly?",{"A":46,"Q":47},"Openings cover NLP, computer vision, content safety, LLM training and evaluation, RLHF pipelines, and general data labeling. Some roles emphasize QA evaluation, dataset curation, or prompt writing and testing.","What domains can I work in?",{"A":49,"Q":50},"Remote contract, freelance, full-time, part-time, and internships. Entry-level and junior roles are most common, with senior opportunities for candidates who progress to lead evaluation, tooling, or data engineering responsibilities.","What employment types are available?",{"A":52,"Q":53},"Create a profile, upload your resume and portfolio links, and use search modifiers such as remote, contract, freelance, full-time, entry-level, or senior. Submit applications directly on Rex.zone and complete any short skills assessments.","How do I apply via Rex.zone?",{"A":55,"Q":56},"Pay varies by employer type, region, and task complexity. Entry-level rates are typically competitive for remote work, with increases tied to technical scope, quality metrics, and sustained performance.","What compensation should I expect?",{"A":58,"Q":59},"Formal experience is not required for many entry-level listings. Demonstrate potential with personal projects, bootcamp work, notebooks, clean code samples, and attention to training data quality and guideline adherence.","Do I need prior experience?",{"A":61,"Q":62},"VS Code, Jupyter, GitHub, issue trackers, Docker, annotation tools like Label Studio or CVAT, and cloud dashboards. Many teams use standardized QA and evaluation frameworks for LLMs and computer vision.","Which tools will I use day to day?",{"A":64,"Q":65},"You can move from junior coder or annotator into QA lead, evaluation engineer, data engineer, or MLOps roles. Success is measured by reliable execution, annotation guidelines compliance, and contributions to model performance improvement.","What does career progression look like?","Entry-Level Coding"]