AI / ML Engineer

Role overview Build the core intelligence behind a new generation of AI operators that run live business workflows rather than just answering questions. As an AI/ML engineer, you will own models, orchestration, and feedback loops, taking agents from prototype to production in domains like hospitality, operations, and sales.

Responsibilities - Design and build multi-agent systems that operate autonomously inside real business environments. - Fine-tune and evaluate large language models for domain-specific tasks, with measurable improvements in quality. - Build retrieval-augmented generation (RAG) pipelines and the knowledge systems that support them. - Develop evaluation frameworks that tie agent behavior to real business KPIs. - Architect prompt chains, tool-use patterns, and the orchestration layers that tie agents together. - Work directly with customers to understand operational needs and turn them into shipped AI capabilities.

Requirements - Three or more years of experience in machine learning or AI engineering. - Hands-on experience with large language models, including fine-tuning, prompt engineering, and evaluation. - Strong Python skills and working knowledge of ML frameworks such as PyTorch and Hugging Face. - Track record of building production ML systems, not just research prototypes. - Familiarity with vector databases, embedding models, and retrieval systems. - Comfort working autonomously and making judgment calls in ambiguous, fast-moving situations.

Nice to have - Experience with multi-agent frameworks such as LangGraph, CrewAI, or AutoGen. - Background in reinforcement learning or RLHF techniques. - Prior work in hospitality, retail, or other physical-world industries. - Exposure to robotics or embodied AI systems.