Python Engineer
hace 1 día
Edinburgh
Python Engineer | 6 Month Contract | (Outside IR35) | Remote, Edinburgh | Starting ASAP Day Rate: Market Rates About the role: The organisation has restructured its IT software delivery to align with key business domains, aiming for enduring development teams with clear product ownership. A dedicated team has been formed to advance digital registration automation by analysing the problem domain and developing solutions for high-volume, low-complexity casework. Key challenges include: • Using OCR and Large Language Models (LLMs) to assess automation risk in deed documents., • Applying LLMs to interpret unstructured content in title sheets for more complex casework. Main Duties: Enhance and expand the production automation service using OCR, Object Detection, and LLM AI for land register applications. Key responsibilities: • Develop components for deed OCR, object detection, and LLM-based title analysis., • Conduct research and spikes to broaden automation scope., • Provide high-quality operational support and maintain robust monitoring, dashboards, and deployment processes., • Drive R&D for innovative automation solutions., • Ensure code quality, testing, and compliance with non-functional requirements (security, performance, accessibility)., • Troubleshoot issues across modern AWS stacks and legacy systems. Commercial experience with AI/ML technology: OCR, Object Detection and LLM analysis implementation Machine Learning & AI Libraries including: • Transformers/Hugging Face for working with pre-trained LLMs, fine-tuning, and inference, • PyTorch for deep learning model development and training, • OpenCV for computer vision tasks and image preprocessing in object detection, • PIL/Pillow for image manipulation and format conversion, • YOLO object detection frameworks Core Python Skills: • Proficiency in Python 3.9+ with understanding of object-oriented programming, decorators, context managers, and async/await patterns, • Data structures and algorithms for efficient data processing and model optimization, • Error handling and debugging using try-catch blocks, logging, and debugging tools Data Processing: • Pandas and NumPy for data manipulation, cleaning, and numerical operations, • SQLAlchemy or psycopg2 for database connectivity and ORM operations, • Boto3 for AWS service integration and automation AWS (working within Technical Lead's architecture): • Lambda function development with proper event handling and response formatting, • S3 operations including multipart uploads, presigned URLs, and event notifications, • CloudWatch logging and metrics for monitoring and debugging, • Understanding of IAM and security for role-based access and credential management, • Experience with CDK for infrastructure deployment, • SQS for message queuing, • EKS/ECS/Kubernetes for containerized AI deployments API Development: • FastAPI for building REST APIs and model serving endpoints, • Requests library for HTTP client operations and external API integration, • Authentication/authorization implementation (JWT, OAuth) Software Development: • Making excellent quality AI/ML software collaboratively with other engineers, • Working effectively under technical leadership while contributing specialized AI/ML expertise, • Design and implementation of AI/ML solutions using service-based and serverless architecture, • Using written, verbal, and visual communication to explain AI/ML concepts to both technical and non-technical audiences, • Development Practices:, • Cloud monitoring, telemetry, intelligence tools for AI/ML systems, including Grafana, • Experience working in Agile delivery models - Scrum and/or Kanban frameworks, • Formal XP engineering techniques including TDD and pair programming, • Working within defined infrastructure-as-code frameworks Development Practices: • Cloud monitoring, telemetry, intelligence tools for AI/ML systems, including Grafana, • Experience working in Agile delivery models - Scrum and/or Kanban frameworks, • Formal XP engineering techniques including TDD and pair programming, • Working within defined infrastructure-as-code frameworks Advanced AI/ML Technologies: • Custom model architecture design and implementation, • Advanced fine-tuning techniques including LoRA, QLoRA, and parameter-efficient methods, • Multi-modal AI systems combining text, image, and structured data, • Reinforcement Learning from Human Feedback (RLHF) for model alignment Production ML Systems: • Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management, • Model versioning and experiment tracking (MLflow, Weights & Biases), • Real-time model serving and edge deployment strategies, • A/B testing frameworks for ML model evaluation This role has been deemed Outside IR35 by the client. Applicants must hold, or be happy to apply for, a valid Basic Disclosure Scotland. Please click the link to apply.