Python Developer

Overview

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.

• 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.
• 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 Num Py for data manipulation, cleaning, and numerical operations.
• SQL Alchemy 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.
• Cloud Watch 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.
• FastAPI for building REST APIs and model serving endpoints.
• Requests library for HTTP client operations and external API integration.
• 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.
• 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.
• 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.

• Seniority level:
  Mid-Senior level
• Employment type:
  
  Contract
• Job function:
  Analyst
• Industries:
  Information Services

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