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.
• Automating wet signature verification through document analysis, object detection, and open language models.

The team focuses on improving the scope and accuracy of automation solutions, working closely with other business domains to ensure integration with existing platforms and alignment of roadmaps for production deployment.

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.
• Apply collaborative practices (pairing, mobbing, code reviews) and actively engage in team events and wider communities of practice.

Essential Skills & Experience:

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

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.