Python Developer

Venesky-Brown’s client, a public sector organisation in Edinburgh / Glasgow, is currently looking to recruit a Python Engineer for an initial 6 month contract with potential to extend on a rate of £569/day (Outside IR35). This role will be a hybrid of working at home and in the office. Responsibilities: - Research and development of novel solutions that enable the organisation’s automation goals. - Demonstrate excellent, sustainable, and collaborative software development practice that’s focused on delivering highly readable, maintainable, and appropriate artefacts. - Extend and sustain the high-quality support procedures, dashboards, monitoring and deployment capabilities to ensure the team can continue to improve services via feedback. - Actively participating in all team events, leading where specialist knowledge is required, and supporting the team to improve their process through inspection and adaptation. - Engage with the wider communities of practice and interest to share knowledge, techniques, and experience. - Ensure high quality of developed solutions through development and maintenance of unit tests – with appropriate code coverage – and code analysis using code quality tools. - Ensure that developed software complies with non-functional requirements, such as accessibility, security, UI/UX, performance, maintainability, deployability, etc... - Troubleshoot development and production problems across multiple environments and operating platforms, from the AWS-based modern stack to the multiple strands of ETL and database (legacy and otherwise) that underpins the service. - Routinely use collaborative development practices such as pairing and mobbing techniques in programming, code reviews, system design and requirements analysis/refinement, etc. - Coaching and mentoring other team members, as appropriate. Essential Skills: - 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 and YOLO object detection frameworks - 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 - 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 - 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 - FastAPI for building REST APIs and model serving endpoints - Requests library for HTTP client operations and external API integration - Authentication/authorization implementation (JWT, OAuth) - 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 - 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 Desirable Skills: - 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 - 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 If you would like to hear more about this opportunity please get in touch.