
Austin, TX, USA, Remote, USA
Serverless Ventures (www.serverlessvc.com) 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, 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
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.
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.