AI Engineer

Description

Summary: Join the Azuria estimation team as an offshore AI Engineer to enhance and extend an existing AI-powered map extraction system, improving model accuracy and optimizing SaaS workflows. Highlights: 1. Enhance and extend an existing AI-powered map extraction system 2. Customize and fine-tune LLMs and computer vision models for map extraction 3. Operate with minimal supervision in a collaborative, async-first environment **Role Overview** ----------------- This is an offshore AI Engineering role embedded within the Azuria estimation team to enhance and extend an existing AI\-powered map extraction system. The engineer will work closely with estimation leads and cross\-functional stakeholders to improve model accuracy, expand extraction capabilities, and optimize end\-to\-end SaaS workflows. The ideal candidate brings strong applied ML and computer vision experience, comfort working within an existing codebase, and the ability to operate with minimal supervision in a collaborative, async\-first environment. **Key Responsibilities** ------------------------ * Customize and fine\-tune large language models (LLMs) and computer vision models to improve map feature extraction accuracy across diverse input formats (PDFs, scanned drawings, GIS exports) * Extend and optimize the existing AI map extraction pipeline — including pre\-processing, inference, post\-processing, and output validation stages * Collaborate with Azuria's estimation team to translate domain requirements into model improvements and feature enhancements * Design and implement evaluation frameworks (precision, recall, IoU, etc.) to measure model performance and guide iteration * Build and maintain data engineering pipelines for training data ingestion, labeling quality assurance, and dataset versioning * Optimize SaaS platform workflows — reducing latency, improving throughput, and enhancing reliability of AI\-driven outputs within the production application * Participate in code reviews, technical documentation, and knowledge\-sharing with the broader engineering and estimation teams * Monitor model performance in production, identify drift or degradation, and implement retraining or remediation workflows **Required Qualifications** --------------------------- * 4\+ years of hands\-on experience in applied machine learning or AI engineering, with demonstrated work in computer vision or document understanding * Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent) * Experience working with LLMs (fine\-tuning, prompt engineering, RAG architectures) * Familiarity with image processing libraries (OpenCV, Pillow) and geospatial or CAD data formats is a strong plus * Experience with cloud platforms (AWS, GCP, or Azure) and containerized deployment (Docker, Kubernetes) * Solid understanding of data engineering fundamentals — ETL pipelines, data validation, and storage best practices * Ability to work independently in an async\-first, distributed team environment with minimal supervision * Strong written communication skills for technical documentation and cross\-functional collaboration **Preferred Qualifications** ---------------------------- * Prior experience in construction, infrastructure, or utility estimation domains * Familiarity with GIS tools, spatial data, or map digitization workflows * Experience building or maintaining evaluation and monitoring frameworks for ML models in production * Track record of contributing to SaaS products with AI/ML components