Senior Machine Learning Engineer

HSBC Group
London, UK
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

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
+19 more
Tensorflow Software Deployment Software Engineering Data Logging Cloud Platform System Pytorch Flask (Web Framework) Delivery Pipeline Large Language Models Technical Debt Fastapi Containerization AI Platforms Git Flow Kubernetes Machine Learning Operations Api Design Software Version Control Docker

Job description

  • 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

Requirements

  • 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.

Benefits & conditions

As an HSBC employee in the UK, you’ll have access to tailored professional development opportunities and a competitive pay and benefits package. This includes private healthcare for all UK-based employees, enhanced maternity and adoption pay and support when you return to work, and a contributory pension scheme with a generous employer contribution.

About the company

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 realisetheir ambitions., Being open to different points of view is important for our business and the communities we serve. At HSBC, we’re dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, socio-economic background or age. We are committed to removing barriers and ensuring careers at HSBC are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dejobs.org

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · WWC Europe 2026

3:33 min

Connecting frontends via a FastAPI proxy backend layer

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

7:10 min

Exploring pathways into the machine learning engineering field

Jose Luis Latorre Millas · LIVE

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

Videos

See all

Related articles

See all