Software Engineer, AI/ML

Role responsibilities

Own the intelligence layer by building AI agents, evaluation frameworks, and inference pipelines to detect and explain product failures. Develop context engineering systems and anomaly detection to turn runtime data into actionable insights for product teams.

Requirements

Candidates must have experience shipping production-grade ML or LLM systems and the ability to move rapidly from research to working prototypes. Strong proficiency in agent architectures, tool use, and a rigorous approach to measurement and evaluations is required.

Key skills

Machine Learning, Large Language Models, Agent Architectures, RAG, Anomaly Detection, Context Engineering, Program Analysis, Evaluation Frameworks, Inference Pipelines, Retrieval Systems, Python, System Design, Software Engineering, Root-Cause Analysis, Autonomous Workflows, Time-Series Modeling

Keywords

AI/ML, LLM, Agents, Evals, Inference Pipelines, RAG, Retrieval, Indexing, Anomaly Detection, Time-Series Modeling, Program Analysis, Code Understanding, Root-Cause Analysis, Triage, Sandboxes, Model Routing, Observability, Feedback Loops, Context Construction, Production ML, Y Combinator, Vercel Ventures, Software Engineering, System Design, Agentic Workflows, Runtime Data, Traces, Logs, Product Quality, New York City