Applied Scientist

Haize Labs gets LLM apps out of POCs and into production. We eliminate the risk and improve the reliability of LLM apps by haizing them – i.e. rigorously, proactively, and continuously fuzz-testing them. We are looking for Research Engineers to help develop our reliability platform, with a focus on: Data-efficient alignment of evaluation models Dynamic testing of AI applications Observability and anomaly detection Discrete optimization (with applications in architecture search and automated prompting) Our work is both intellectually stimulating and practically in high demand. Your work will result in net-new primitives, frameworks, and algorithms for developing robust LLM applications. You work will directly influence how LLM apps are tested, verified, and deployed everywhere. You will directly influence how the world responsibly uses LLMs. Responsibilities Develop optimization, synthetic data generation, and fuzzing methods for breaking LLM systems. Implement complex automated evaluation models and systems. Go from research idea to code within hours; and iterate quickly on experiments and data. Work directly with customers to adapt our tools for different domains. Qualifications First-author publications in top-tier ML venues (NeurIPS, ICML, ICLR, and others). Bias for action & experimentation over philosophizing (though sometimes good). Not interested in printing papers for papers' sake. Some production engineering experience (e.g. ML in an applied setting). No spaghetti research code! Some familiarity with ideas from active learning, weak supervision, synthetic data, functional verification, reinforcement learning, reward modeling, automated evaluation. A subset of this is fine. Annual Salary $150,000 – $600,000 USD Logistics Location policy: In NYC. US visa sponsorship: If you are exceptional, we will sponsor. Compensation and Benefits: We provide generous salary, equity, and benefits #J-18808-Ljbffr