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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Scientist - **Company:** Hackajob Ltd - **Location:** Leeds, UK - **Experience:** Expert - **Salary:** £61,000.0 - £101,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Code Review, Databases, Continuous Integration, Data Integration, DevOps, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, Release Management, Tensorflow, Standard Sql, Software Deployment, Software Engineering, Data Logging, Pytorch, Flask (Web Framework), Delivery Pipeline, Model Validation, Technical Debt, Git, Fastapi, AI Platforms, Git Flow, Kubernetes, Machine Learning Operations, Api Design, Software Version Control, Docker, Web Api - **Published:** September 30, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5898221844 ## About the Role * Strong software engineering experience delivering end-to-end services in production, with ownership for run/support considerations * Proficiency in Python and modern engineering practices, including clean code, testing, packaging, dependency management, and Git-based workflows * Hands-on experience with AI deployment patterns and infrastructure, such as Docker, Kubernetes, API-based serving, and batch/stream inference * Practical MLOps experience, including CI/CD for ML, model packaging and release management, automated validation, monitoring, and lifecycle management * Working knowledge of ML/DL frameworks and tooling, such as PyTorch, TensorFlow, and the Python ML ecosystem, to collaborate effectively with data scientists and implement inference pipelines * Experience working with complex, multi-layered datasets, including imbalanced data, and integrating data pipelines into AI services * Hands-on experience building and deploying web APIs using libraries such as Flask or FastAPI * Proficiency with database technologies such as SQL Server or Postgres * Strong stakeholder communication skills, with the ability to explain technical designs, risks, and operational considerations to technical and non-technical audiences * Good organisational skills and delivery discipline, including prioritisation, time management, and working across multiple initiatives * Degree in a relevant field or equivalent practical experience, with a Masters preferred * Model explainability approaches or tools, such as SHAP, where required by the use case and governance expectations ## Description * Design, build, deploy, and operate production-grade AI services, including ML and/or GenAI, that are secure, scalable, and reusable across Wholesale use cases * Productionise PoC and PoV work into hardened solutions with clear non-functional requirements, including performance, resilience, cost, and security, and defined service ownership * Build and maintain MLOps and LLMOps pipelines, including CI/CD, automated testing, packaging, promotion and rollback, and model/version management, to enable repeatable releases * Develop reusable engineering assets, such as libraries, templates, reference architectures, and infrastructure-as-code patterns, to reduce technical debt and accelerate delivery * Implement observability for AI services, including logging, metrics, tracing, model performance monitoring, and quality or drift checks with actionable alerting * Partner with data scientists, data engineers, platform teams, and governance or risk stakeholders to ensure end-to-end delivery meets control, auditability, and documentation expectations * Translate business requirements into technical designs and communicate trade-offs and recommendations clearly to technical and non-technical stakeholders * Contribute to engineering standards and ways of working, including code reviews, design reviews, and documentation, and help uplift team capability through practical coaching Technologies: * AI * API * CI/CD * Docker * FastAPI * Flask * Git * Support * Kubernetes * Machine Learning * MLOps * Network * PyTorch * Python * SQL * Security * TensorFlow * Web ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Shifting Stress to Progress— Understanding DevOps to do DevOps Better](https://www.wearedevelopers.com/videos/268-shifting-stress-to-progress-understanding-devops-to-do-devops-better) - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)