Member of Technical Staff (Machine Learning Engineer, Search & Agents)

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three—training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. You’ll help turn that freedom into better systems, taking ideas from experiments through training and evaluation to production. RESPONSIBILITIES - Push search and agent quality forward through improvements to models, training data, tools, and system design. - Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. - Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. - Design and build agent harnesses: the tools, context man... Click Apply to read the full job description.