Computer Vision EngineerAsh Technologies was founded in 1994 to design and manufacture a range of award-winning electronic magnifiers for the visually impaired. In 2013, Ash decided to apply its innovation and design skills to digital vision and inspection for industry. Based in Naas, Co. Kildare, we have built our reputation for agile innovation, designing, and manufacturingdigital inspection systemsthat enable our target market businesses thrive in a complex environment where inspection, accuracy, tracking, and traceability are intrinsic to our partner's development and growth. Our philosophy is simple; we are curious, we work hard, we are passionate about what we do, and we provide value to our partners through successful delivery and support of our unique solutions. We believe in working closely with our target markets and industries to ensure that our solutions and platforms are relevant and simple to use. Having recently developed and launched ASH's Machine Learning and Artificial Intelligence platforms for industry, we are growing the team to support the growing demand for ASH's solutions for Industry. Role OverviewWe are seeking a Computer Vision Engineer to join our team. This role sits at the intersection of computer vision, machine learning, and production ready software engineering, contributing directly to the development of advanced visual inspection systems.You will work closely with software, embedded, and hardware engineers to design, implement, and deploy vision algorithms that operate in real-world industrial environments. The role involves both algorithm development and practical system integration, with an emphasis on reliability, performance, and maintainability.Key ResponsibilitiesDesign, implement, and optimise computer vision and image processing pipelines for industrial inspection applicationsDevelop and deploy machine learning and deep learning models for defect detection, classification, and measurementWork with Python and C++ codebases across Linux-based systemsIntegrate vision algorithms with embedded and edge-based hardware platformsCollaborate with cross-functional teams including embedded systems, electronics, optics, and product engineeringEvaluate algorithm performance using appropriate metrics and datasets; iterate based on real-world resultsContribute to system architecture, code reviews, and technical documentationSupport the transition of R&D solutions into production-ready softwareRequired Skills & ExperienceDegree in Computer Science, Software Engineering, Electronic/Electrical Engineering, Applied Physics, or a related disciplineProfessional experience in computer vision and image processingStrong programming skills in Python and C++Experience developing on Linux-based systemsPractical experience with OpenCV and image processing techniquesFamiliarity with machine learning / deep learning frameworks (e.g. PyTorch, TensorFlow)Solid understanding of data structures, algorithms, and object-oriented designStrong analytical and problem-solving skillsAbility to work independently while collaborating effectively within a multidisciplinary teamDesirable / Additional ExperienceExposure to real-time or performance-constrained systemsExperience working with camera sensors, optics, and lighting, including an understanding of how imaging hardware and acquisition conditions affect algorithm performanceFamiliarity with agile development methodologiesExperience with version control, CI/CD pipelines, and software quality practicesPersonal AttributesComfortable working in a customer-facing role, able to engage with clients and clearly communicate technical concepts in a professional mannerWell-organised, with the ability to manage multiple tasks and prioritiesCollaborative, curious, and solution-orientedHigh level of integrity and professionalism when handling confidential informationAdaptable to evolving project requirements and customer-driven developmentPackage & BenefitsCompetitive salary with performance-related bonusCompany pension and life coverVHI healthcareHoliday loyalty schemeCareer progression and further education supportBike to Work schemeFlexible working model (hybrid remote / onsite)Supportive, technically strong team environment