Machine Vision and AI Engineer

What we offer

We are seeking a highly skilled and experienced Machine Vision and AI Engineer to join our dynamic Data Science department. This role will be pivotal in developing, testing, and deploying cutting-edge machine vision and artificial intelligence algorithms to enhance our global electronics repair operations. The successful candidate will leverage their expertise to create innovative solutions for tasks such as automated defect detection, component identification, machine learning, process optimization, and more. You will be expected to lead projects, mentor junior team members, and contribute significantly to the strategic direction of our machine vision initiatives.

The position will suit a flexible, self-starter, who is passionate about technology, and has an ability to develop on a variety of projects and maintenance depending on demands. The ideal candidate will be confident working and communicating with stakeholders at all levels, across global locations, in an impactful manner.

Your tasks

• Focus of this role is development and testing of machine vision systems
• Algorithm Development and Implementation: Design, develop, and implement advanced machine vision algorithms using Python and relevant libraries (e.g. OpenCV, scikit-image, NumPy, SciPy, Pandas, etc) to address specific business challenges within electronics repair.
• Lead data-driven decision making process by collaboration with stakeholders and subject matter experts across the organization
• Drive business strategic decisions by translating large and complex datasets into clear, actionable insights.
• Machine Learning & Deep Learning model development, with focus at machine vision application: Build, train, and evaluate deep learning models using frameworks such as TensorFlow, PyTorch, or Keras for complex image analysis tasks, including object detection, classification, and segmentation.
• Data Acquisition and Preprocessing: Collaborate with relevant teams to define data requirements, oversee data collection processes. Implement robust data cleaning, augmentation and preprocessing pipelines for machine vision models.
• Model Evaluation and Validation: Develop and implement rigorous testing and validation methodologies to ensure the accuracy, reliability, and performance of machine vision algorithms. This includes defining relevant metrics, creating test datasets and conducting thorough evaluations.
• Deployment and Integration: Lead the deployment of developed algorithms and models into production environments, ensuring seamless integration with existing systems and infrastructure. This will involve working with cloud platforms such as AWS EC2, Amazon Sagemaker AI, edge computing devices and internal APIs.
• Performance Optimization: Continuously monitor and optimize the performance of deployed machine vision systems, identifying and resolving bottlenecks and ensuring scalability and efficiency.
• Collaboration and Communication: Effectively communicate technical findings and insights to both technical and non-technical stakeholders. Collaborate closely with cross-functional teams, including operations, engineering, and IT, to understand business needs and translate them into technical solutions.
• Research and Innovation: Stay updated on emerging technologies, tools, and best practices in machine vision, AI and related technologies. Proactively research and evaluate new methodologies, tools, and libraries to improve our capabilities and explore innovative solutions for the electronics repair domain.
• Technical Leadership and Mentorship: Provide technical guidance and mentorship to junior data scientists and engineers within the team. Lead specific projects, define technical specifications, and ensure adherence to best practices.
• Documentation: Create comprehensive documentation for developed algorithms, models, deployment processes, and system architectures.
• Project ownership: Take ownership of data science projects from conception to deployment and create new tools to support the business need to drive value from the data.
• Working in an agile manner, constantly seeking the most efficient methods to deliver against business objectives, delivering rapid insights and proof of concepts to teams.
• Mentor junior team members and contribute to the development of data science capabilities within the organization
• Follow version control best practices, develop and maintain documentation on projects, methods and code base.
• Highly proficient in spoken and written English