Teams at hum.ai

Own the architecture and research direction of AI models for earth observation and remote sensing data. Develop and evaluate novel approaches, define success metrics, scale experiments to petabyte-level training, integrate models with agent-based products, plan research roadmaps, and publish findings. The role requires strong AI research expertise, experience shipping AI systems, and comfort modeling non-language data such as images, time series, and sensor data.

Own the machine learning platform supporting experiment tracking, distributed multi-node training, model evaluation, and production inference. Build reliable, reproducible, and cost-efficient systems that scale from small experiments to petabyte-scale multimodal training. Collaborate with research scientists, data and software engineers, and product teams to integrate models with downstream agents. Develop training and inference interfaces, support multimodal data, and optimize performance, observability, and infrastructure costs.

This is an open application opportunity for candidates whose skills do not match a currently listed role. Applicants should submit a resume and a brief note describing the type of work they would like to pursue. The company will consider candidates for suitable future opportunities as they become available.