About this role
Salary: £61,000 - 101,000 per year
Requirements: Strong software engineering experience delivering end-to-end services in production, with ownership for run/support considerationsProficiency in Python and modern engineering practices, including clean code, testing, packaging, dependency management, and Git-based workflowsHands-on experience with AI deployment patterns and infrastructure, such as Docker, Kubernetes, API-based serving, and batch/stream inferencePractical MLOps experience, including CI/CD for ML, model packaging and release management, automated validation, monitoring, and lifecycle managementWorking 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 pipelinesExperience working with complex, multi-layered datasets, including imbalanced data, and integrating data pipelines into AI servicesHands-on experience building and deploying web APIs using libraries such as Flask or FastAPIProficiency with database technologies such as SQL Server or PostgresStrong stakeholder communication skills, with the ability to explain technical designs, risks, and operational considerations to technical and non-technical audiencesGood organisational skills and delivery discipline, including prioritisation, time management, and working across multiple initiativesDegree in a relevant field or equivalent practical experience, with a Masters preferredModel explainability approaches or tools, such as SHAP, where required by the use case and governance expectations Responsibilities: Design, build, deploy, and operate production-grade AI services, including ML and/or GenAI, that are secure, scalable, and reusable across Wholesale use casesProductionise PoC and PoV work into hardened solutions with clear non-functional requirements, including performance, resilience, cost, and security, and defined service ownershipBuild and maintain MLOps and LLMOps pipelines, including CI/CD, automated testing, packaging, promotion and rollback, and model/version management, to enable repeatable releasesDevelop reusable engineering assets, such as libraries, templates, reference architectures, and infrastructure-as-code patterns, to reduce technical debt and accelerate deliveryImplement observability for AI services, including logging, metrics, tracing, model performance monitoring, and quality or drift checks with actionable alertingPartner with data scientists, data engineers, platform teams, and governance or risk stakeholders to ensure end-to-end delivery meets control, auditability, and documentation expectationsTranslate business requirements into technical designs and communicate trade-offs and recommendations clearly to technical and non-technical stakeholdersContribute to engineering standards and ways of working, including code reviews, design reviews, and documentation, and help uplift team capability through practical coaching Technologies: AIAPICI/CDDockerFastAPIFlaskGitSupportKubernetesMachine LearningMLOpsNetworkPyTorchPythonSQLSecurityTensorFlowWeb More:
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.
last updated 39 week of 2026