AI / ML Engineer Intern: (LLM & Agentic AI)
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Reach the decision-maker — $5About the role
**Horrazon AI**
We're looking for one exceptional person — not a class of interns. If you've actually trained, fine\-tuned, or built something real with LLMs and you're ready to prove it in production, keep reading.
**Why Horrazon**
Every business runs on data it doesn't have time to read. We're building **Pogee**, our own LLM, and the agent layer around it, to fix that – ingesting live data from Instagram, Facebook, LinkedIn, YouTube, and X and turning it into decisions a founder can act on in seconds, not a report they skim once a month.
We're pre\-revenue, venture\-track, and backed by Nvidia Inception, AWS Startup, Zoho Startup, and others. Small team, high leverage, no bureaucracy. What you ship this month is live for real customers next month.
**The Bar**
We're not hiring someone to call an API and wrap a prompt. We're hiring someone who understands what's happening *inside* the model — who's trained something from scratch, fine\-tuned an open\-source model with a real technique, and can reason about why it worked or didn't.
You don't need five years of industry experience. You need to have gone deep enough—through projects, research, or competitions—that you can defend your choices, not just repeat them.
**What You'll Own**
* **Training \& Fine\-Tuning** — Fine\-tune open\-source LLMs using LoRA/QLoRA, full fine\-tuning, and preference\-optimization techniques (RLHF/DPO\-style) for real product use cases. * **Model Fundamentals** — Bring real understanding of transformer architecture, tokenization, pretraining objectives, and training dynamics — this is what separates you from a prompt engineer. * **Agentic Systems** — Design and build the reasoning and decision layer of our agents: multi\-step planning, tool use, and pipelines that turn raw data into plain\-English recommendations. * **Evaluation** — Build rigorous evals, run controlled experiments, and make evidence\-backed calls on what ships — no vibes\-based deployment. * **Data Engineering for Training** — Work across our Python/Go/PostgreSQL stack to prepare and structure high\-quality training and fine\-tuning datasets from multi\-platform social and ads data. * **Efficiency** — Own inference cost, latency, and quantization decisions. We're pre\-revenue — every GPU\-hour matters.
**Who We're Looking For**
* Pursuing or recently completed a degree in CS, AI/ML, Data Science, or equivalent — but your project history matters more than your GPA. * Demonstrated, hands\-on experience training or fine\-tuning LLMs — PyTorch, Hugging Face Transformers/PEFT, and at least one real project involving pre\-training or fine\-tuning, at any scale. * Deep, working knowledge of transformer internals: attention, embeddings, loss functions, tokenization — you should be able to explain these from first principles, not just cite them. * Real exposure to agentic AI — building or experimenting with tool\-calling, multi\-step reasoning, or orchestration frameworks (LangChain, LlamaIndex, or your own custom stack). * Strong Python; comfortable with SQL and REST/OAuth2 API integration. * Git\-fluent, writes clean and documented code, and communicates with precision in an async, remote\-first environment.
**Strongly Preferred**
* Multi\-GPU or distributed training experience or hands\-on model quantization work. * Open\-source contributions to ML/LLM projects, competitive ML rankings (Kaggle, etc.), or published research. * Familiarity with Go, PostgreSQL, or social platform APIs (Meta, LinkedIn, YouTube, X).
**What You Get**
* **Direct access to the CTO** — no management layers, no filtered feedback, real technical mentorship. * **Production ownership from day one** — your models and agents run live, serving real customers. * **A rare, compounding skillset** — full\-cycle LLM training paired with agentic system design is a combination almost no internship offers. * **An honest reference** — specific, real, and earned. * **A fast track to full\-time** — priority consideration for a full\-time offer as we scale.
**How to Apply**
Email **careers@horrazon.in** Subject: **AI / ML Engineer Intern: (LLM \& Agentic AI)** *— \[Your Full Name]*
Include:
* Your CV/resume (PDF). * 3–5 sentences on why LLMs and agentic AI, specifically — and why now, with us. * Links to real work — GitHub, Kaggle, papers, fine\-tuning projects, anything that proves you've built and broken things. * Your available start date and confirmation you can commit to the schedule.
We respond within 3 business days. If you're not sure you meet the bar but you know you can, apply anyway and show us.
***Horrazon Intelligence Private Limited***
Pay: Up to ₹10,000\.00 per month
Benefits:
* Cell phone reimbursement * Flexible schedule * Internet reimbursement * Paid sick time * Work from home
Work Location: Remote
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