AI Research Scientist

Description

The company is working out how the Earth changes by building a world model of the whole planet. The model represents how Earth processes behave, forecasts what a place will look like next, and makes that understanding useful.

Founded at the University of Waterloo and backed by HF0, Climactic, Onto Ventures, and angels from Firebase and OpenTable, the company has raised over $10M from firms including HF0, Climactic, Inovia Ventures, Onto Ventures, and angels from Firebase and OpenTable. It is a small, technical, collaborative team of PhDs and engineers who have built and shipped at scale, tackling some of the largest unsolved problems.

Engineers are building pipelines to ingest petabytes of earth observation and remote sensing data, plus an agent that uses that data and the models to answer customer questions.

Customers in nature conservation, carbon removal, and government use the models to protect ecosystems and respond to a changing climate. The company takes positive impact seriously, including safety and guardrails.

Responsibilities

• Own the core model: review the current approach, understand why it was chosen, and change it when the evidence calls for it.
• Decide with the Chief Scientist what the model learns from the data and how, and work with engineers on training, experiments, and getting models into customer use.
• Apply cutting-edge techniques to reveal the meaning in large, unusual datasets, and connect that to downstream performance with domain experts.
• Help define what gets measured. The company is not chasing existing GeoAI benchmarks.
• Test ideas in quick, low-cost experiments, then scale the strongest ones to petabyte-scale training with engineers.
• Work with the agent team on how the model is called, what it returns, and how to make it more useful in the product.
• Set milestones, roadmap, and resourcing with leadership, and flag risks early.
• Publish research on earth observation foundation models and present the work at conferences and to the wider community.

Requirements

• PhD in computer science, engineering, or a related field, or equivalent experience.
• 2+ years of industry experience building and shipping AI systems.
• Deep knowledge of cutting-edge AI research, shown through original ideas or meaningful contributions in publications or projects.
• Experience taking ideas from small experiments with limited compute and data to performant large-scale training runs.
• Comfortable designing models for data types beyond text.
• Bonus: experience training models on non-language data such as images, time series, or sensor data, ideally geospatial or earth observation, or a background in earth science.
• Bonus: background in math or physics, especially where it informs modelling of physical systems and sensor data.
• Bonus: strong engineering fundamentals, fluent in Python and PyTorch, able to write efficient and reliable training and inference code, and comfortable with agentic coding tools.

Benefits

• Competitive salary.
• Meaningful early-stage equity, reflecting that you would be one of the first AI hires.
• Health, dental, and vision coverage.