Senior Machine Learning Scientist

• 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

• 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

We are partnering directly with HSBC to hire a Senior Machine Learning Scientist. HSBC is one of the largest banking and financial services organisations in the world, with a network covering more than 50 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and helping people fulfil their hopes and realise their ambitions. We offer opportunities, support, and rewards that can help you go further in your career. We are committed to diverse and inclusive workplaces and to removing barriers so careers are accessible for everyone. We also support disability inclusion and will offer an interview to candidates with disabilities, long-term conditions, or neurodivergent candidates who meet the minimum criteria for the role.