Software Engineer

About Maneva 
Maneva, a startup founded by an ex-Google Deepmind researcher, is an AI service provider revolutionizing manufacturing operations with cutting-edge AI solutions for autonomous factory operation and optimization. Our solution generates AI-powered actions and insights using off-the-shelf hardware or existing vision systems for real-impact manufacturing problems in products and equipment inspection, production efficiency, safety, and more. 

What You'll Do 

As a Software Engineer at Maneva, you will focus on building, deploying, and supporting AI software systems that power customer-facing deployments. You’ll work closely with Deployment Engineers, Systems Design, ML, and Infrastructure teams to ensure Maneva’s software runs reliably in real-world industrial environments.

This role is highly practical and execution-oriented. You will develop and maintain deployment-ready software stacks, implement custom modules or services required for specific customer applications, and ensure systems meet performance, reliability, and operational requirements across edge and cloud environments.

About Maneva Maneva, a startup founded by an ex-Google Deepmind researcher, is an AI service provider revolutionizing manufacturing operations with cutting-edge AI solutions for autonomous factory operation and optimization. Our solution gener...

Key Responsibilities 

• Support software deployment for customer projects, across edge and cloud environments
• Build and maintain custom software modules, services, and integrations required for specific customer applications
• Develop and operate backend services and infrastructure supporting real-time vision and AI systems
• Optimize software performance for real-time inference, low latency, and resource-constrained environments
• Support deployment pipelines, configuration management, and versioned releases
• Collaborate with Deployment Engineers to debug and resolve issues in live production environments
• Implement monitoring, logging, and observability to ensure system reliability and uptime
• Contribute to CI/CD pipelines, testing, and deployment automation
• Document software configurations, deployment processes, and customer-specific customizations
• Support and extend user-facing interfaces that interact with deployed AI applications, including dashboards, controls, and operational tooling
• Collaborate with backend, deployment, and ML teams to integrate frontend applications with edge and cloud services
• Support edge device fleet operations, including activity tracking, health monitoring, and deployment status visibility across customer sites

What We're Looking For 

Must-Haves 

• 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
  

Nice-to-Haves 

• 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

About Maneva 
Maneva, a startup founded by an ex-Google Deepmind researcher, is an AI service provider revolutionizing manufacturing operations with cutting-edge AI solutions for autonomous factory operation and optimization. Our solution generates AI-powered actions and insights using off-the-shelf hardware or existing vision systems for real-impact manufacturing problems in products and equipment inspection, production efficiency, safety, and more. 

What You'll Do 

As a Software Engineer at Maneva, you will focus on building, deploying, and supporting AI software systems that power customer-facing deployments. You’ll work closely with Deployment Engineers, Systems Design, ML, and Infrastructure teams to ensure Maneva’s software runs reliably in real-world industrial environments.

This role is highly practical and execution-oriented. You will develop and maintain deployment-ready software stacks, implement custom modules or services required for specific customer applications, and ensure systems meet performance, reliability, and operational requirements across edge and cloud environments.

About Maneva Maneva, a startup founded by an ex-Google Deepmind researcher, is an AI service provider revolutionizing manufacturing operations with cutting-edge AI solutions for autonomous factory operation and optimization. Our solution gener...

Key Responsibilities 

• Support software deployment for customer projects, across edge and cloud environments
• Build and maintain custom software modules, services, and integrations required for specific customer applications
• Develop and operate backend services and infrastructure supporting real-time vision and AI systems
• Optimize software performance for real-time inference, low latency, and resource-constrained environments
• Support deployment pipelines, configuration management, and versioned releases
• Collaborate with Deployment Engineers to debug and resolve issues in live production environments
• Implement monitoring, logging, and observability to ensure system reliability and uptime
• Contribute to CI/CD pipelines, testing, and deployment automation
• Document software configurations, deployment processes, and customer-specific customizations
• Support and extend user-facing interfaces that interact with deployed AI applications, including dashboards, controls, and operational tooling
• Collaborate with backend, deployment, and ML teams to integrate frontend applications with edge and cloud services
• Support edge device fleet operations, including activity tracking, health monitoring, and deployment status visibility across customer sites

What We're Looking For 

Must-Haves 

• 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
  

Nice-to-Haves 

• 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