Hybrid Machine Learning Engineer (Roofing Technology sphere) Machine Learning Engineer (Roofing Technology sphere)

The customer is a forward-thinking startup in the roofing industry, dedicated to transforming traditional practices through innovative technology. They aim to revolutionize how roofing companies handle roof inspections, particularly focusing on automating the process of identifying roof brands and models, especially in cases of damage. Their mission is to simplify and expedite the assessment of roof damage by integrating advanced AI technology, ultimately streamlining operations for roofing professionals and improving accuracy in roof evaluations.

Project Description

The Project Aims To Develop An MVP That Enhances Roofing Companies' Efficiency In Assessing Roof Damage And Identifying Shingle Types. It Includes

• Mobile Application: A cross-platform app for field use, allowing users to capture and analyze photos of roof shingles to quickly identify the roof's brand and model.
• Web Application: A platform with various user roles for managing accounts, subscriptions, and company settings, serving as the backend for the detection process.
• Machine Learning Engine: A core component trained on client-provided data to detect and classify shingles, integrated into both the mobile and web applications for accurate identification.

Technologies

• TensorFlow (including Keras)
• PyTorch
• Computer Vision Techniques
• Image Processing
• Python
• OpenCV
• Pillow
• AWS
• Azure
• Data Preprocessing
• Feature Engineering
• Model Evaluation

What You'll Do

• Participate in technical design sessions to identify/document technical solutions;
• Collaborate with stakeholders to understand the specific computer vision challenges the project aims to solve;
• Design/train deep learning models for classification and object detection;
• Configure AWS services to deploy and manage computer vision models;
• Communicate technical project requirements, progress, and outcomes to non-technical stakeholders, ensuring clear understanding and alignment;
• Oversee the image annotation process, ensuring high quality annotations critical to model training;
• Develop and implement evaluation metrics to assess the performance of object detection and segmentation models;
• Conduct thorough testing to ensure models meet the required standards;

Job Requirements

• 4+ years' experience in machine learning, computer vision, and software development;
• Proficiency in Deep Learning frameworks such as TensorFlow (including Keras) and/or PyTorch (PyTorch is a preference);
• Understanding of computer vision techniques and image processing;
• Experience with Python and relevant libraries (e.g., OpenCV, Pillow);
• Experience with cloud platforms (e.g., AWS, Azure);
• Knowledge of data preprocessing, feature engineering, and model evaluation;
• Possession of an AWS certification will be a plus;
• Level of English - from Upper-Intermediate+ (spoken/written);

What Do We Offer

The Global Benefits Package Includes

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.