Senior Software Engineer - Data

Location: SF or Waterloo, with ability to travel
Start Date: Flexible, ideally July 1 2025

We are seeking an experienced backend engineer to join our team and help us build a digital twin of the natural world. The successful candidate will be responsible for supporting the design, building, monitoring, and maintenance of the data pipelines and related tooling for large-scale AI model training and inference.

Who are we?

HUM.AI is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we’re backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations.

What do we do?

We’re building a multimodal foundation model for the physical world. We believe there’s more to the world than the internet and more to intelligence than learning language. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the physical world.

About the role

We are seeking a software engineer to help us build a digital twin of the natural world. To do this, we need fast access to large and diverse geospatial datasets. The focus of this role is on building the software, systems, and data stores needed to prepare these data for AI model training and inference at scale. This is primarily a backend role, responsible for the design, building, monitoring, and maintenance of the underlying pipelines, databases, tooling, and related applications.

The role will involve:

• Earth observation data pipeline design and implementation, with a focus on scalability and performance

• Building and maintaining a multi-Petabyte data lake for diverse geospatial and ancillary datasets

• Close collaboration with the AI research team to explore options, develop requirements, and assess results

• Laying a foundation of s sound engineering practice to support future growth

• Sharing responsibility for cloud computing infrastructure for distributed data pipeline components

• Ad-hoc support for visualization and demos

Requirements

• Bachelor’s degree in engineering, computer science or a related field, or equivalent

• 5+ years of relevant experience

• Demonstrated experience with managing, ingesting, and transforming geospatial data

• Fluency with Python programming

• Experience building data pipelines and tooling to support downstream applications, including containerization and orchestration technologies such as Docker and Airflow, or equivalent

• Comfort with managing and scaling up cloud computing infrastructure and services

• Familiarity with databases and SQL

• Team player, willing wear various hats and go beyond the job description

Nice to have

• Familiarity with the open source cloud geospatial ecosystem e.g. STAC, ODC

• Knowledge of Earth observations and methods including satellite remote sensing and weather reanalysis data

• Proficiency in PyTorch and/or Ray

• Knowledge of AWS networking and security protocols

• Familiarity with object store databases like Redshift/Snowflake

• Experience with creating infrastructure for AI

• Location wise, strong preference for in-person in Waterloo, however hybrid work is possible for exceptional candidates