San Francisco
2 months agoJob Overview
Job Type
InternPay
Not disclosedJob description
- Location:
- San Francisco, United States
- Work arrangement:
- On-site
Role Summary
Duration: 3 months, with a possibility of a full-time job afterwards
Start date: immediately
WHAT WE CAN'T OFFER
- Hands-on supervision. We're around for brainstorming and high-level guidance, but you own your work and will be the person who knows it best.
- A well-defined project. We're early-stage and led by customer and market pull, so we work on several directions at once. You'll navigate this alongside the rest of us.
- Training wheels. After a short onboarding, you'll work on hard, customer-facing, time-sensitive problems like everyone else. Not a typical internship.
We're running a tight ship on a rough sea. Not for everyone, but you'll come out the other side a much stronger sailor.
Requirements
ABOUT YOU
- You love research, read papers and hack on new repos for fun
- Comfortable training ML models/transformers and doing independent applied research
- Excellent Claude Code (or similar) user
- Highly ambitious, ready for high-intensity YC startup culture, self-motivated
- Strong communicator, fast response time, team player
PREFERRED
- LLM research experience, shown through publications, open-source contributions, or personal projects
- BSc or MSc in CS/DS, math, or physics.
- Startup or research internship experience (industry or academic)
Benefits
- Competitive compensation
- All the resources you need: GPUs, subscriptions, OpenAI/Anthropic credits
- As much responsibility as you can handle. Our goal is to make you an irreplaceable part of the team
- A fast-paced environment where you'll learn much faster than usual, surrounded by technical people who push each other
- Possibility of a full-time offer based on performance
About the Company
- We're building state-of-the-art context compression. Our mission is to become the "Cloudflare for LLMs", a compression layer embedded into most LLM pipelines by default.
- We're a team of ex-EPFL MSc/PhDs. We started by publishing papers, then got into YC and started making money helping companies cut their LLM costs.
- We run the business like a research lab: form hypotheses, kill the ones that don't work, double down on the ones that do.
Additional Information
- A 40-minute call: 20 minutes for introductions and motivations, followed by 20 minutes of technical questions (mostly ML/LLM foundational questions)
- A paid take-home project designed to take around 6 hours, followed by a 30-minute call to walk us through your work and answer a few questions
- A 30-minute culture interview with the whole team
- Offer
- Role:
- Research Intern
- Job Type:
- Intern
Company profile
compresr
compresr.aiCompresr is an LLM context-compression API: users send long context plus a query and get back a shorter context that keeps the answer-bearing tokens and drops the rest, cutting token cost and latency. It is available through a Python SDK, TypeScript SDK or hosted HTTP API. Compresr Inc. is run by a team of ex-EPFL MSc/PhDs who went through YC, and aims to become the Cloudflare for LLMs.
- Founded
- 2026