Job Description
Automation Systems Engineer Role Summary
This role offers the opportunity to play a key part in driving efficiency across industries and contributing to the development of cutting-edge AI solutions.
The ideal candidate will have experience owning production-grade systems from design through deployment and support, with expertise in software development methodologies such as Agile or Scrum processes.
* Key Responsibilities:
* Embedded Software Development: Design and build robust applications across front-end and back-end platforms, focusing on scalability and maintainability.
* Work with GStreamer pipelines, open-source vision models, Git, and Docker: Collaborate with various tools and technologies to optimize hardware use for machine vision workloads and support the full development cycle.
* Code Quality, Version Control, & Deployment: Write efficient, testable code and manage repositories using Git, then deploy using tools like Docker.
* Production Control: Identify and resolve critical bugs and production issues quickly and independently.
* System Assembly: Lead the build of machine systems, guiding technicians through both mechanical assembly and electrical wiring.
* Project Documentation: Accurately complete ISO9001 documentation, including requirement specs, bills of materials, and testing and reporting records.
* Team Leadership: Provide technical leadership by onboarding and mentoring new team members, including acting as a lead for junior engineers.
Required Skills and Qualifications
* Software Development Expertise: 5+ years in a hands-on systems engineering role using Python, ideally in a startup or small-team environment.
* Educational Background: Master's Degree in Computer Engineering, or Mechatronics / Electronics or a related technical field.
* Specialised Knowledge: AI technologies, machine learning frameworks, open-source vision tools such as Open CV and YOLO.
* Software Tools: Experience with GIT and Docker.
* Initiative: Proven ability to work independently and show initiative in a fast-paced environment.
* Mentorship: Experience supporting or mentoring junior engineers.
* Dev Ops: Familiarity with Dev Ops practices and tools (e.g., Git, CI/CD, Docker) is an advantage.
Benefits
* Career Advancement: Structured mentorship and clear pathways for career development in software engineering.
* Cutting-Edge Technology: Work on innovative, award-nominated AI solutions that are shaping the future of manufacturing and automation.
* Training & Development: Access to ongoing training to deepen your technical expertise in AI, machine vision, and software development.
* Collaborative Team Culture: Join a dynamic and supportive team that values your ideas and contributions.