Edge AI Developer for Industrial Automation

Saicon; Redmond; On-site; AUD 120,000 - 180,000; Full time

Job summary

Saicon in Australia is seeking an Innovation AI Developer II to design, develop, and deploy AI-powered software for industrial production. You will own end-to-end delivery from requirements to edge deployments on embedded systems, integrating computer vision, NLP, and predictive analytics.

Responsibilities include building AI models for edge devices, optimizing latency and memory, mentoring junior developers, leading POC demos for customers, and evaluating new AI tools to boost team

Qualifications

• Bachelor's degree in a relevant field; Master's preferred.
• 2–5 years of AI development or software engineering with demonstrated project ownership.

Responsibilities

• Design and develop end-to-end AI-powered software applications for industrial use cases.
• Build and deploy AI models to edge devices, embedded systems, and offline environments.
• Own the full software development lifecycle: architecture, implementation, testing, deployment.
• Develop internal AI agents and automation tools to improve operational efficiency.
• Collaborate with cross-functional teams to gather requirements and deliver solutions.
• Optimize model performance for production: inference latency, memory footprint, accuracy.
• Set up and maintain customer demonstrations using IPCs, HMIs, cameras, sensors, PLCs.
• Mentor junior developers through code reviews and technical guidance.
• Evaluate and integrate emerging AI technologies and OOB tools for team productivity.
• Lead POC development and deliver demos to customers and stakeholders.

Skills

Python

C++

Java

Go

Rust

Docker

FastAPI

Flask

Git

CI/CD

PyTorch

TensorFlow

Computer Vision

NLP

LangChain

LangGraph

ONNX

TensorRT

Education

Bachelor's degree

Master's degree

Tools

Claude Code

Cursor

Job description

Saicon in Australia is seeking an Innovation AI Developer II to design, develop, and deploy AI-powered software for industrial production. You will own end-to-end delivery from requirements to edge deployments on embedded systems, integrating computer vision, NLP, and predictive analytics.

Responsibilities include building AI models for edge devices, optimizing latency and memory, mentoring junior developers, leading POC demos for customers, and evaluating new AI tools to boost team