Senior embedded engineer developing safety - critical ECU firmware for Hexagon Mining’s digital mining and vehicle - control technologies. Designing, testing, and commissioning embedded systems.
About the role
- Software Engineer at Maneva focusing on AI software for customer-facing deployments in manufacturing. Collaborating with engineering teams to deploy and maintain efficient solutions.
Responsibilities
- 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
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
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