Senior Machine Learning and AI Engineer

Senior Machine Learning and AI Engineer

Job type:

Full-time (Hybrid Remote)

Responsibilities

·       Algorithm Development and Implementation: Design, develop, and implement advanced machine vision and AI 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: 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 and AI models.

·       Model Evaluation and Validation: Develop and implement rigorous testing and validation methodologies to ensure the accuracy, reliability, and performance of machine vision and AI 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 and AI 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

Required Experience and Skills

·       Bachelor's degree in Data Science, Computer Science, Software Engineering / Information Technology or a related discipline.

· years of technical experience working on machine vision and AI projects.

·       Proven practical experience with analysing large amounts of complex imagery using machine vision techniques and/or AI to obtain clear, actionable insights.

·       Hands-on experience in development different machine vision methods and AI algorithms, including most popular model architectures and frameworks from most popular CNN architectures image classification and feature extraction to object detection (R-CNN, YOLO) and image segmentation.

·       Familiarity with emerging technologies in the field of machine vision models and AI, such as vision transformers, foundation models (incl. stable diffusion, Segment Anything, etc)

·       Experience with development and practical application of machine learning methods for regression, classification and NLP.

·       Proficiency in use of Python and Python IDEs (Anaconda, VS Code, Jupyter or similar) for analytics and data science.

·       Hands-on experience with data visualization tools and frameworks, e.g. Matplotlib, Seaborn, Pillow or similar.

·       Familiarity with code version control, CI/CD and collaboration tools, e.g. GitHub, GitLab, AWS CodePipeline, JIRA or similar

·       Familiarity with database technologies (e.g., SQL, NoSQL) and data manipulation techniques.

·       Familiarity with using cloud computing platforms, e.g. AWS, GCP or Azure, for ML & AI.

·       Excellent communication, presentation and influencing skills.

·       Proven project management skills and capable of carrying projects through to completion.

Preferred Experience and Skills

·       Proficiency in use of at least one other programming language widely used in the filed of machine vision and AI, such as C++, C#/.NET or Java.

·       Knowledge of Lean Six Sigma methodologies and principles for process improvement.

·       Experience working in manufacturing or service sectors.

·       Certifications in statistics, machine vision, machine learning/AI, or related disciplines

·       Significant experience with using AWS for machine vision or AI.

·       Master's degree or Ph.D. in Data Science, Computer Science, Software Engineering / Information Technology or a related discipline.