[Hiring] AI Research Scientist @hum.ai

Role Description

As our AI Research Scientist, you'll own the model at the center of our system. Our engineering team is building the pipelines that ingest petabytes of earth observation and remote sensing data, and an agent that uses that data and our models to answer customer questions. You’ll work closely with our Chief Scientist to decide what the model learns from that data and how, and with our engineers to train and experiment and put your models to good use for our customers and the world.

• Own the architecture.
• Evaluate our current approach, understand the thinking behind it, and change it where the evidence says to.
• Figure out what the data knows.
• Apply state-of-the-art techniques to uncover the semantics of large, unusual datasets and turn that into downstream performance, working with domain experts.
• Define success.
• We aren't chasing existing GeoAI benchmarks. You'll help decide what we measure.
• Go from small to large.
• Prove ideas in fast, cheap experiments, then scale the winners to petabyte-scale training with our engineers.
• Shape the integration.
• Work with the agent team on how the model gets called, what it returns, and how to make it more useful in the product.
• Plan the path.
• Set milestones, roadmap, and resourcing with leadership, and spot risks early.
• Share what you learn.
• Write up and publish research on earth observation foundation models, and represent our work at conferences and with the broader community.

Qualifications

• PhD degree in computer science, engineering, a related field, or equivalent experience.
• 2+ years of industry experience building and shipping AI systems.
• Deep understanding of cutting edge AI research, with a track record of original ideas or meaningful contributions shown through publications and/or projects.
• Experience taking ideas from small, exploratory experiments in compute- and data-limited settings to performant, large-scale training runs.
• Comfortable designing models for unconventional data modalities beyond “just text”.

Requirements

• Experience training models on non-language data (images, time series, sensor data), ideally geospatial or earth observation, or a background in earth science.
• Background in math or physics, especially where it informs how you model physical systems and sensor data.
• Strong engineering fundamentals: fluent in Python and PyTorch, and able to write efficient, reliable training and inference code, and comfortable using agentic coding tools.

Benefits

• Work that matters for the planet.
• A team worth joining.
• Well backed.
• Competitive salary, meaningful early-stage equity, health, dental and vision.
• As one of the first AI hires, your equity stake reflects that.