AI Researcher Intern

Serverless Ventures () is hiring an AI Researcher Intern to explore the cutting edge of AI 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.

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.

Remote, USA

Austin, TX, USA (local preferred)

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

• 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

• 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

• 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,
    Lang Chain
    , or similar tooling

  • Academic paper reading and literature synthesis

  • Built applications using Hermes Agent, Deer Flow, Open Claw etc.

• Strong analytical thinking and written communication

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

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

• 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

• 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

• 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.

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.