Machine learning engineer in AI services

HSBC; Greater London; On-site; GBP 120,000 - 150,000; Full time

Benefits offered by this job

Private healthcare for UK employees

Enhanced maternity and adoption pay

Contributory pension scheme

Job summary

HSBC Holdings plc приглашает опытного Senior Machine Learning Engineer в Growth AI программу в рамках CIB Data & Analytics. Ваша задача — разрабатывать и разворачивать производственные ML/GenAI сервисы, обеспечивать инфраструктуру и управлять жизненным циклом моделей в облаке.

Работа предполагает тесное взаимодействие с данными учёными и командами платформы. Требуется практический опыт в MLOps, знание Python, Docker, Kubernetes, FastAPI/Flask, и умение объяснять технические решения

Qualifications

• Опыт разработки производственных ML/GenAI сервисов.
• Уверенное владение Python и современными практиками кодирования (чистый код, тестирование, упаковка).
• Опыт MLOps: CI/CD, упаковка моделей, мониторинг, управление жизненным циклом моделей.

Responsibilities

• Разработка, развёртывание и эксплуатация производственных ML/GenAI сервисов.
• Преобразование PoC/PoV в надёжные решения с учётом требований к производительности, устойчивости, затратам и доступу.
• Разработка MLOps пайплайнов и инфраструктуры как код.
• Сотрудничество с учёными данными, инженерами данных и командами платформы.
• Обеспечение соответствия требованиям контроля и аудита.

Skills

Python

ML/GenAI

CI/CD

API Development

Tools

Docker

Kubernetes

FastAPI

Flask

SQL/DBs

Job description

Описание

We’re currently seeking an experienced professional to join our team in the role of Senior Machine Learning Engineer. As our Senior Machine Learning Engineer you’ll join the Growth AI programme within Corporate & Institutional Banking (CIB) Data & Analytics. Growth AI is a key pillar of the Insights and Analytics space within CIB Data & Analytics. Our focus is to develop AI applications that identify new business opportunities, identify risks of client attrition, and enhance our collective capabilities to serve our customers.

Задачи

• 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

Требования

• 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)
• Proven track record designing, deploying and operating production ML/GenAI services in cloud environments, understanding the operational realities vs on‑prem (security, networking, scaling, resilience and cost management).
• Hands on experience building agentic LLM systems, including RAG workflows, tool/function calling and orchestration, and integrating external APIs and enterprise data sources to improve business operations with appropriate guardrails and evaluation.

Условия

As an HSBC employee in the UK, you’ll have access to tailored professional development opportunities and a competitive pay and benefits package.

• private healthcare for all UK-based employees
• enhanced maternity and adoption pay and support when you return to work
• contributory pension scheme with a generous employer contribution