Augmodo is building the "operating system for the physical shelf" using spatial computing and wearable AI. We provide real-time, store-level insights that were previously impossible to capture. We are moving fast, and we need an applied engineer who combines real Computer Vision expertise with high-velocity front-end tooling to make complex spatial data instantly intuitive and highly actionable.

The Challenge

We are looking for a Software Engineer to own the end-to-end user interfaces, active learning agents, and visual tooling powering our Spatial Platform. This is not just a front-end tools role—it requires a real Computer Vision background. You will leverage your experience building and deploying shippable CV models to build pre-labeling agents, custom models for active learning, functional editors, and model-training environments.

Because you understand what it takes to train production-grade ML models, you know that high-quality data is everything. You will apply that knowledge directly to building optimized, intelligent annotation and curation tools for our internal researchers, algorithms, and external clients.

Key Responsibilities

• Applied CV for Tooling & Automation: Train and integrate lightweight, custom CV models, active learning workflows, and pre-labeling agents specifically designed to accelerate human annotation and data quality control.

• Data Curation & Annotation Systems: Build robust internal QC, mapping, and annotation platforms (akin to autonomous vehicle curation pipelines) backed by an intimate understanding of CV data quality and edge cases.

• Spatial & Planogram Interfaces: Design high-performance front-end interfaces that map raw product images and computer vision metadata directly to physical coordinates on digital retail planograms.

• High-Velocity Iteration: Build functional editors, POCs, and pre-labeling pipelines rapidly to support active model development. We value high agency—shipping high-quality features in days, not months.

• Consumer-Facing Simplicity: Translate complex, multi-layered spatial and ML outputs into simple, intuitive visual workflows for non-technical users.

Basic Requirements

• Computer Vision Background: Hands-on experience building, training, and deploying real-world CV models to production. You understand end-to-end model lifecycles and know what "high-quality data" actually looks like.