Applied Research Engineer

Labelbox•San Francisco, CA

5d•$250,000 - $300,000•Hybrid

About The Position

Applied Research at Labelbox builds the benchmarks and data that drive the next generation of foundational agentic capabilities. We are looking for exceptional researchers and research engineers to join our team to measure and improve agent performance while collaborating directly with our frontier lab research partners. We are committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.

Requirements

2+ years of industry experience in ML, with an MS, PhD, or equivalent research track record in CS / ML / a related field.
Track record of published papers in top venues (e.g. NeurIPS, ICML, ACL, EMNLP)
Strong understanding of experimental design, statistical analysis, and evaluation frameworks
Self-directed individual with strong communication skills

Responsibilities

Define benchmarks and training signals to push agentic capabilities forward.
Conduct research to ensure evaluations and data are insightful and reliable.
Propose and collaborate on experiments and projects with research teams at frontier labs for their evaluation and training needs.
Drive ambiguous research threads autonomously.
Turn research insights into concrete opportunities.
Stay current with the latest developments in agentic capabilities, training, and evaluation methodologies.
Publish research findings and contribute to the broader research community.