Spatial AI Engineer

Careers Engineering

Spatial AI Engineer

Job Description

About BigGeo

BigGeo is the Spatial Cloud.

We help companies manage and access the world’s spatial data.

Any size, any slice, any insight.

Delivered in seconds.

We’re building something that hasn’t existed before : a new layer of the internet where the “where” and “when” behind every decision is instantly clear, programmable, and actionable. Our platform removes the complexity that has kept spatial data locked in silos for decades and replaces it with speed, precision, and control.

We’re a Calgary-based company, early and moving fast, with real customers, real infrastructure, and a clear point of view on where the world is going.

Why BigGeo Exists and Why People Build Here

Most companies are spatially blind. They know what their data says, but not where or when things actually happen. That gap costs real money, creates real risk, and limits what AI can actually do in the physical world.

BigGeo exists to close that gap.

We’re not building another tool. We’re building the rails that connect the planet’s moving data to the systems that run the world. That’s a big problem, and it takes people who care about doing things right, not just fast.

People build here because :

The problem is real and the category is open. We’re not competing for the middle of an existing market, we’re defining a new one. Your work shapes what the category becomes.

Your fingerprints are on the architecture. We’re at the stage where the decisions you make today become the foundation tomorrow. What you ship matters.

We run on clarity, not politics. We move with purpose. No bureaucratic drag, no HiPPO decisions, just a team that agrees on the mission and gets to work.

You’ll grow fast because the problems are hard. Spatial data at scale is a genuinely difficult domain. If you want to be stretched, you’ll be stretched.

We’re building for longevity. We’re not chasing hype cycles. We’re building infrastructure, the kind that compounds in value over time and earns the trust of the companies that depend on it.

The Role

The Spatial AI Engineer builds the systems that let AI models, applications, and intelligent agents understand and reason about the real world through spatial data. You will design and implement machine learning systems that operate directly on spatial datasets inside The Spatial Cloud, turning raw location and time data into intelligence that applications and AI agents can act on in seconds.

This role sits at the intersection of machine learning, spatial computing, and large-scale data infrastructure. You will build the models, pipelines, and inference services that make spatial intelligence operational : not research artifacts sitting in notebooks, but production systems answering real questions at global scale.

You will work alongside Core Systems Engineers building the Spatial Cloud platform, data platform engineers managing global spatial datasets, and product teams shipping spatial intelligence capabilities to developers and enterprises. The problems are hard, the datasets are enormous, and the impact is visible, because what you build is used in real‑world environments.

If you want to build AI systems that reason about the physical world and shape a new category of infrastructure as it takes form, this is the place to do it.

What You Will Build and Own

As a Spatial AI Engineer, you will contribute to and own systems that include :

Spatially‑aware machine learning models that incorporate geometry, location, and temporal context as first‑class inputs.

AI‑powered spatial analytics and pattern detection systems that find signal in global‑scale geospatial data.

Spatial reasoning systems that understand how places, movements, and events relate across space and time.

Training and evaluation pipelines for spatial AI models, including dataset management, labeling workflows, and reproducible experiments.

Real‑time spatial inference services that deliver model outputs to applications and agents with low latency at scale.

APIs and services that let developers, applications, and AI agents query spatial intelligence directly from The Spatial Cloud.

Key Responsibilities

Spatial AI Model Development

Design, train, and iterate on machine learning models that operate on spatial and spatio‑temporal datasets.

Build models that detect patterns, relationships, and anomalies across geospatial signals, from dense urban data to sparse global datasets.

Experiment with spatial reasoning approaches that incorporate location, geometry, and temporal context as explicit features, not afterthoughts.

Evaluate model accuracy, calibration, reliability, and operational behavior against real production workloads.

Data Engineering and Pipelines

Build pipelines for ingesting, cleaning, transforming, and preparing spatial datasets for machine learning.

Manage training datasets, versioning, and evaluation frameworks with the rigor of a production system.

Ensure spatia