Machine Learning Engineer, AI Agents

People In AI is a venture-backed technology platform building next-generation AI systems for complex workflows. The role involves owning the design and deployment of production AI systems, including building multi-agent systems and developing scalable infrastructure for real-world applications.

Responsibilities:

• Build and scale multi-agent systems powering copilots and workflow automation
• Design end-to-end AI architectures across retrieval, reasoning, tool use, and validation
• Develop orchestration frameworks, including memory, state management, and tool routing
• Own evaluation frameworks focused on reasoning quality, hallucination reduction, and correctness
• Deploy and maintain distributed, low-latency AI systems in production
• Contribute to platform-level decisions across model serving, infrastructure, and system design

Requirements:

• Proven experience shipping LLM-powered or AI products into production environments
• Strong experience with multi-agent systems and orchestration frameworks
• Deep understanding of RAG, memory systems, and tool-calling architectures
• Hands-on experience with post-training techniques (LoRA, DPO, GRPO, or similar)
• Strong Python and distributed systems engineering background
• Experience building and operating systems in cloud production environments
• Ability to operate autonomously in a fast-paced, low-structure environment