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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Scientist - **Company:** HSBC Group - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Automation of Tests, Code Review, Databases, Continuous Integration, Data Integration, DevOps, Python (Programming Language), PostgreSQL, Machine Learning, Microsoft SQL Server, Release Management, Tensorflow, Software Deployment, Software Engineering, Data Logging, Pytorch, Flask (Web Framework), Delivery Pipeline, Technical Debt, Fastapi, Containerization, AI Platforms, Git Flow, Kubernetes, Machine Learning Operations, Api Design, Software Version Control, Docker - **Published:** August 18, 2026 - **Apply:** https://dejobs.org/x/x/265E08A665034121B09ABCA4DCDED381/job/ ## About the Role * Strong software engineering experience delivering end-to-end services in production (not just notebooks/experiments), with ownership for run/support considerations * Proficiency in Python and modern engineering practices (clean code, testing, packaging, dependency management, Git-based workflows) * Hands-on experience with AI deployment patterns and infrastructure (e.g. containerisation with Docker, orchestration such as Kubernetes, API-based serving, batch/stream inference) * Practical MLOps experience: CI/CD for ML, model packaging and release management, automated validation, monitoring, and lifecycle management * Working knowledge of ML/DL frameworks and tooling (e.g. PyTorch/TensorFlow and the Python ML ecosystem) sufficient 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, etc. * Strong stakeholder communication skills: able to explain technical designs, risks, and operational considerations to wide-ranging audiences * Good organisational skills and delivery discipline (prioritisation, time management, working across multiple initiatives) * Degree in a relevant field or equivalent practical experience (Masters highly preferred) * Model explainability approaches/tools (e.g. SHAP) where required by use case and governance expectations (desirable) ## Description If you're looking for a career that will help you stand out, join HSBC, and fulfil your potential - whether you want a career that could take you to the top, or an exciting new direction, we offer opportunities, support and rewards that will take you further. We're one of the largest banking and financial services organisations in the world, with a network that covers more than 50 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people fulfil their hopes and realise their ambitions. We are seeking aSenior Machine Learning Scientist You'll play a key part indesigning, building, deploying, and operating production-grade AI services (ML and/or GenAI) that are secure, scalable, and reusable across Wholesale use cases In this role you'll: * Design, build, deploy, and operate production-grade AI services (ML and/or GenAI) that are secure, scalable, and reusable across Wholesale use cases * Productionise PoC/PoV work into hardened solutions with clear non-functional requirements (performance, resilience, cost, security) and defined service ownership * Build and maintain MLOps/LLMOps pipelines (CI/CD, automated testing, packaging, promotion/rollback, model/version management) to enable repeatable releases * Develop reusable engineering assets (libraries, templates, reference architectures, infrastructure-as-code patterns) to reduce technical debt and accelerate delivery * Implement observability for AI services (logging/metrics/tracing), model performance monitoring, and quality/drift checks with actionable alerting * Partner with data scientists, data engineers, platform teams, and governance/risk stakeholders to ensure end-to-end delivery meets control, auditability, and documentation expectations * Translate business requirements into technical designs; communicate trade-offs and recommendations clearly to both technical and non-technical stakeholders * Contribute to engineering standards and ways of working (code reviews, design reviews, documentation) and help uplift team capability through practical coaching ## Related Videos - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Multilingual NLP pipeline up and running from scratch](https://www.wearedevelopers.com/videos/901-multilingual-nlp-pipeline-up-and-running-from-scratch) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) ## 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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)