Applied Research Intern

Labelbox

San Francisco, California, United States
Base: $35-$45 usd annual; equity: not specified; b...
On-site
Ph.d. or master's in computer science
Deep understanding of frontier multimodal models
Proficiency in python and pytorch/jax/tensorflow
You will design and build evaluation suites for reasoning, code, agents, and vision-language models while creating post-training datasets at scale

Job Summary

  • You will design and build evaluation suites for reasoning, code, agents, and vision-language models while creating post-training datasets at scale.
  • The role offers the opportunity to prototype RLHF/RLAIF training loops and land research directly into customer-facing product features.
  • Labelbox operates like an early-stage startup where you will take on expanded responsibilities quickly with clear ownership and career growth tied to your impact.

Matching Summary

You will design and build evaluation suites for reasoning, code, agents, and vision-language models while creating post-training datasets at scale.

Salary

Base: $35-$45 USD annual; Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • Ph.D. or Master's in Computer Science
  • Deep understanding of frontier multimodal models
  • Proficiency in Python and PyTorch/JAX/TensorFlow
  • Experience with LLM evaluation and benchmarking
  • Track record of publishing in top-tier AI conferences

Nice-to-have

  • Passion for bridging research and application
  • Exceptional communication and collaboration skills
  • Ability to work in a high-impact startup environment
  • Experience with human-AI interaction techniques

Key Requirements

  • Ph.D. or Master's degree in progress acceptable
  • Publication record in NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL
  • Expertise in training data quality construction and refinement

Work Rights

Not specified

Tailored Resume

Cover Letter