Machine Learning Engineer
🤖Senior Machine Learning Engineer | Financial Services & AI 🤖
🌐Data & AI Global Consulting Firm 🌐
📍 London, Hybrid
💸 £90k - £110k plus bonus
We're partnering with a leading AI consultancy that has spent over a decade helping some of the world's most sophisticated organisations deploy machine learning and AI into production. Their Financial Services practice is experiencing significant growth and is looking for a Senior Machine Learning Engineer to help deliver large-scale AI systems across banking, insurance, asset management and broader financial markets.
This is not a research or data science role.
We're looking for engineers who understand that successful AI products are built on strong software engineering foundations. The ideal candidate will combine deep machine learning expertise with a proven track record of building reliable, scalable production systems within regulated financial environments.
You'll work directly with clients to design and deploy production-grade AI solutions that solve commercially critical problems, operating at the intersection of machine learning, software engineering, cloud infrastructure and financial services.
What You'll Be Doing
- Designing and building production-grade machine learning applications and platforms
- Developing scalable software systems that enable AI products to operate reliably in highly regulated environments
- Leading technical architecture discussions and influencing engineering best practices
- Working closely with stakeholders across technology, product and commercial functions
- Translating complex business challenges into robust AI-powered solutions
- Mentoring engineers and contributing to a culture of engineering excellence
What We're Looking For
- Strong software engineering background with expert-level Python development experience
- Experience building, deploying and maintaining production machine learning systems
- Proven track record operating within financial services, fintech, banking, insurance or capital markets environments
- Deep understanding of cloud-native architectures and modern engineering practices
- Hands-on experience with containers, Kubernetes and scalable distributed systems
- Ability to engage confidently with both technical teams and senior business stakeholders
Why This Role?
The most successful machine learning systems in financial services are rarely won by better models alone. They're won by engineers who can combine software engineering rigour, machine learning expertise and a strong understanding of the operational realities of regulated financial environments.
If you've built production systems, understand the demands of financial services, and want to work on high-impact AI deployments rather than endless proofs of concept, we'd love to hear from you.
#MLE #machinelearning #SWE