Software Engineer

Role Overview

• Focus on building, deploying, and supporting AI software systems that power customer-facing deployments
• Work closely with Deployment Engineers, Systems Design, ML, and Infrastructure teams
• Develop and maintain deployment-ready software stacks
• Implement custom modules or services required for specific customer applications
• Ensure systems meet performance, reliability, and operational requirements across edge and cloud environments

Requirements

• Degree in Computer Science, Software Engineering, or equivalent industry experience
• Strong experience supporting production software deployments and feature development
• Experience with cloud and/or edge infrastructure, including Linux-based systems
• Solid backend development skills in Python, C/C++, or equivalent
• Experience with implementing image processing and computer vision applications with tools such as OpenCV
• Familiarity with DevOps practices: CI/CD, containerization, configuration management
• Ability to debug issues across application code, infrastructure, and runtime environments
• Strong collaboration skills with hardware, deployment, and customer-facing teams
• Willingness to travel to customer deployments in Canada and the United States as needed
• Full-stack or frontend web development experience, particularly with TypeScript and React, to support user interfaces and operational tools for deployed AI applications
• Prior experience working with fault-tolerant edge AI systems in production environments
• Experience with edge fleet management, including device provisioning, lifecycle management, health monitoring, and remote updates
• Familiarity with tracking edge device activities, telemetry, logs, and operational metrics across distributed deployments
• Experience deploying and maintaining software on distributed, intermittently connected, or resource-constrained edge devices
• Experience with real-time systems or low-latency applications
• Expertise in inference optimization (model serving, performance tuning, hardware acceleration)
• Familiarity with Docker, Kubernetes, or lightweight orchestration at the edge
• Exposure to monitoring and observability tools (Prometheus, Grafana, ELK, etc.)
• Experience working in industrial, robotics, or manufacturing environments
• Prior work in startup or fast-paced customer-facing engineering teams

Tech Stack

• Cloud
• Docker
• Grafana
• Kubernetes
• Linux
• Prometheus
• Python
• React
• TypeScript

Benefits

• Build software powered by cutting-edge AI that runs in real factories, not just dashboards
• Own deployment-critical systems with direct customer impact
• Work across edge, cloud, and real-time AI systems
• Collaborate with world-class engineers and AI researchers in a fast-growing startup