STEM Careers India

STEM Careers India on Rex.zone connects Mid-Senior engineers with Remote, Full-Time roles that support AI/ML training workflows, including RLHF, data labeling, QA evaluation, prompt evaluation, and scalable LLM training pipelines. You will collaborate with distributed teams to improve training data quality, enforce annotation guidelines compliance, and drive model performance improvement across NLP and computer vision annotation, content safety labeling, and named entity recognition. This page is designed for candidates exploring technology jobs and for hiring teams recruiting for India-aligned STEM talent through Rexzone.

Job Heading

Title: STEM Careers India Engineer

LinkedIn Job Metadata

About the Role

You will work on Remote, Full-Time engineering programs aligned to STEM careers in India, supporting AI/ML training operations from data collection and data labeling to RLHF evaluation and quality assurance. The work includes implementing annotation tooling, building evaluation harnesses, reviewing prompt evaluation outcomes, and partnering with stakeholders to improve training data quality for large language model evaluation. You will help operationalize annotation guidelines compliance, measure inter-annotator agreement, and iterate workflows that drive model performance improvement.

Key Responsibilities

Design and improve LLM training pipelines for supervised fine-tuning and RLHF; Build and maintain annotation tooling, task routing, and QA evaluation checks; Define labeling taxonomies for NLP tasks like named entity recognition and text classification; Support computer vision annotation workflows including bounding boxes, polygons, and segmentation QA; Run prompt evaluation and rubric-based model evaluation to identify failure modes; Implement content safety labeling policies and escalation paths; Create annotation guidelines, audits, and sampling plans to ensure annotation guidelines compliance; Analyze training data quality metrics, disagreement patterns, and error distributions; Collaborate with cross-functional teams to translate product goals into measurable evaluation criteria; Document decisions, datasets, and evaluation artifacts for traceability and reproducibility.

Required Qualifications

Mid-Senior experience in engineering, data operations engineering, or applied ML workflows; Hands-on experience with data labeling systems, QA evaluation, or model evaluation pipelines; Familiarity with RLHF concepts and large language model evaluation methods; Working knowledge of NLP tasks (classification, NER) and/or computer vision annotation; Ability to write clear annotation guidelines and enforce rubric consistency; Strong communication skills for remote collaboration and stakeholder alignment.

Preferred Qualifications

Experience building internal tools for annotation, auditing, and reviewer workflows; Understanding of content safety labeling, policy taxonomies, and risk-based QA; Familiarity with prompt evaluation methods and adversarial testing; Experience with dataset governance, versioning, and evaluation benchmarks; Exposure to vendor management or BPO-style annotation operations at scale.

Work Setup

Remote role marked Remote; Full-Time employment; Collaboration across time zones with India-aligned STEM talent; Engineering ownership of workflow reliability, data quality, and evaluation rigor.

How to Apply

Apply through Rex.zone and search using modifiers such as remote, full-time, contract, freelance, entry-level, or senior to match your availability. Highlight experience in training data quality, annotation guidelines compliance, QA evaluation, RLHF, prompt evaluation, NLP, computer vision annotation, and content safety labeling.

Frequently Asked Questions

Q: What does “STEM Careers India” mean on Rex.zone?
It refers to Remote, Full-Time engineering roles aligned to STEM talent based in or connected to India, focused on AI/ML training workflows such as data labeling, RLHF, and large language model evaluation.
Q: Is this role remote and full-time?
Yes. The job metadata specifies Remote Type: Remote and Employment Type: FULL_TIME.
Q: What kind of AI/ML work is included?
Common work includes training data quality improvements, annotation guidelines compliance, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, content safety labeling, and RLHF-oriented evaluation for LLM training pipelines.
Q: What experience level is targeted?
Mid-Senior candidates, with prior experience shipping engineering solutions or running scalable data and evaluation workflows.
Q: Which job modifiers does this page support for search?
It covers remote, full-time, contract, freelance, entry-level, and senior, plus domain areas like NLP, computer vision, content safety, and LLM training.
Q: How is quality measured in these workflows?
Through QA evaluation sampling, rubric consistency checks, inter-annotator agreement, audit trails, and metric-driven monitoring of training data quality and model performance improvement.
Q: What tools or skills should I highlight?
Highlight AI/ML evaluation, RLHF awareness, data labeling systems, prompt evaluation, dataset governance, NLP/NER, computer vision annotation, and building reliable LLM training pipelines.
Q: Where do I apply?
Apply via Rex.zone under Rexzone listings and use keyword searches that match your strengths (e.g., RLHF evaluation, data labeling, QA evaluation, NLP, computer vision annotation, content safety).

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