GlitterLabs | AI Researcher Intern | 1+ YoE

Glitter Technology Ventures Pvt. Ltd. (www.glitterlabs.com) is hiring a AI Researcher Intern to build AI-native systems at the intersection of Edge AI, Vertical AI, and large-scale software and content generation.

We're looking for someone who thinks rigorously, ships fast, and brings genuine intellectual curiosity to hard problems. Not someone waiting to be assigned a paper to read, someone already reading them.

If you care about how models actually work, and want to see your ideas land in production systems, keep reading.

About the Role

This is a hands-on, high-curiosity research role with real engineering exposure.

You will work directly with founders and core engineering to design, build scalable, production-grade systems from scratch, investigate, prototype, and validate ideas that shape our AI systems.

As an intern, you are expected to:

• Operate independently

• Take ownership of research questions from framing to findings

• Communicate clearly, written, verbal, and in code

• Move fast without sacrificing rigor
  

We move fast. Deadlines are real. Quality is non-negotiable.

Location

Remote, India

Nagpur, MS, India (local candidates preferred)

We work in person or remote with speed, clarity, and tight feedback loops.

What You’ll Do

• Survey and synthesize research across LLMs, agents, multimodal systems, and edge inference

• Run experiments and prototype novel AI approaches

• Evaluate model performance, benchmark outputs, and identify failure modes

• Translate research findings into actionable engineering recommendations

• Collaborate directly with founders and engineers on open research questions

• Contribute to internal documentation, technical memos, and research reports

Responsibilities

• Stay current with AI/ML literature and distill what matters

• Design and run structured experiments with clear hypotheses

• Identify gaps between state-of-the-art research and production reality

• Communicate findings with rigor and clarity

• Take full ownership of assigned research tracks and deliver on timelines

• Surface insights proactively, don't wait to be asked

Skills We’re Looking For

• Strong foundation in one or more: Python, Go, Rust, PyTorch, JAX

• Solid understanding of:

  • Machine learning fundamentals

  • Transformer architectures and LLM internals

  • Evaluation methodologies

• Experience or coursework in:

  • NLP, computer vision, or reinforcement learning

  • Loop Engineering, Prompt engineering, fine-tuning, or RAG pipelines

• Familiarity with:

  • Hugging Face ecosystem, LangChain, or similar tooling

  • Academic paper reading and literature synthesis

  • Built applications using Hermes Agent, Deer Flow, OpenClaw etc.

• Strong analytical thinking and written communication

• Exposure to cloud platforms (AWS, GCP, Azure) a plus

• Open-source contributions or a public research/GitHub presence a plus

Experience

• Currently pursuing or recently completed a BS/MS/PhD in a relevant field

• Research experience through coursework, labs, or independent projects

• Any prior internship or project involving AI/ML systems preferred

• Track record of seeing ideas through from question to result

Qualifications

• Bachelor's or Master's student (or recent graduate) in Computer Science, AI, Mathematics, or related field

• PhD candidates welcome

• Strong portfolio of projects, papers, or code accepted in lieu of credentials

• Genuine, sustained engagement with the AI/LLM ecosystem is expected baseline

Why Join Us

• Research that actually ships into production

• High ownership from day one

• Work directly with founders

• No bureaucracy, no slow cycles

• Real systems, real users, real impact

• Fastest way to level up if you can keep up

Most researchers summarize papers. We're looking for researchers who challenge them.

If that sounds like you, let's talk.

Note: 

Please answer the questions below using the STAR (Situation, Task, Action, Result) format. Be specific, concise, and quantify impact wherever possible. 

We read these responses carefully and use them to understand how you think, execute, and create meaningful outcomes.