AI Engineer jobs in India on Rex.zone focus on building, evaluating, and deploying production AI systems for real-world NLP and computer vision workflows. You will contribute to LLM training pipelines, RLHF evaluation, prompt evaluation, data labeling quality, and QA evaluation to improve model performance and safety. These roles support AI labs, tech startups, enterprises, BPOs, and annotation vendors, with remote full-time options and cross-functional ownership from dataset strategy to model monitoring. Explore Rex.zone to find AI engineer openings aligned to India-based talent, global teams, and scalable AI delivery.
Title: AI Engineer Jobs in India 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, RLHF, Prompt Evaluation, Data Labeling, QA Evaluation, MLOps, Model Deployment Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR
As an AI Engineer supporting India-based hiring pipelines, you will design and implement ML/LLM features, improve training data quality, and ship reliable model-backed services. You will collaborate with product, data operations, and QA teams to define labeling specifications, annotation guidelines compliance, and evaluation protocols (including RLHF evaluation and prompt evaluation). You will operationalize experiments, track model performance improvement, and ensure safe, measurable releases through testing, monitoring, and iterative dataset refinement.
You will build and maintain ML/LLM components for NLP and computer vision; design evaluation harnesses for large language model evaluation, QA evaluation, and content safety labeling; partner with data labeling teams on taxonomy design, edge-case mining, and training data quality audits; implement RLHF workflows, preference data collection logic, and reward modeling integrations where applicable; create prompt libraries, prompt evaluation suites, and regression tests; deploy models via APIs and batch pipelines, add observability, and run post-deploy error analysis; document experiment results, data provenance, and model limitations for stakeholder review.
LLM training pipelines and dataset curation; named entity recognition and text classification for enterprise workflows; computer vision annotation strategies and active learning loops; content safety labeling and policy-driven evaluation; human-in-the-loop review tooling and QA sampling; offline/online evaluation metrics, calibration, and A/B testing; MLOps automation for training, deployment, monitoring, and rollback.
Mid-senior experience delivering ML systems end to end; strong Python and practical ML engineering skills; experience with NLP, LLMs, or computer vision; familiarity with evaluation methods, error analysis, and dataset quality control; ability to translate product requirements into measurable model goals; comfort working with cross-functional teams spanning engineering, data operations, and QA.
Experience with RLHF, preference data, or prompt evaluation at scale; experience with data labeling operations, annotation tooling, and QA evaluation processes; understanding of content safety labeling and policy-based evaluation; experience with MLOps practices, CI/CD for ML, and model monitoring; strong communication for documenting assumptions, metrics, and trade-offs.
This role is Remote and supports distributed teams. You will collaborate across time zones using clear documentation, async updates, and structured evaluation reports.
Visit Rex.zone and search for "AI Engineer Jobs in India" to explore current openings, compare requirements, and apply to roles that match your ML/LLM background, evaluation experience, and production engineering strengths.
This page targets Remote roles. Individual listings on Rex.zone may include remote, hybrid, contract, freelance, or on-site variants, but this posting is explicitly Remote and full-time.
Common work includes NLP and LLM features, large language model evaluation, RLHF evaluation, prompt evaluation, training data quality improvements, and production deployment with monitoring.
Yes. Many roles partner closely with data operations on data labeling, annotation guidelines compliance, QA evaluation, and feedback loops that drive model performance improvement.
Keyword-aligned skills include Python, machine learning, deep learning, LLMs, NLP, computer vision, RLHF, prompt evaluation, data labeling, QA evaluation, MLOps, and model deployment.
This posting is Mid-Senior and full-time, aligned to engineers who can design evaluation plans, build pipelines, and ship model-backed services.
Rex.zone commonly features roles across AI labs, tech startups, enterprises, BPOs, and annotation vendors, depending on the project domain and model stack.
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