Machine Learning Engineer - FTC

Allica is the UK’s fastest growing company - and the fastest-growing financial technology (Fintech) firm ever. Our purpose is to help established SMEs, one of the last major underserved opportunities in Fintech.

Established SMEs are the backbone of local communities - representing over a third of our economy - yet have been largely neglected both by traditional high street banks and modern fintech providers.

We’re building the next generation of intelligent financial tools for SMEs, starting with an AI-powered Treasurer. Our platform will give business owners real-time visibility across accounts, AI-native cashflow forecasting, and smart treasury optimisations — redefining how small and medium-sized businesses manage money.

We’re looking for a Machine Learning Engineer to join us at the ground floor. Whether you’re an experienced ML engineer who has shipped LLM-powered products or a graduate with exceptional technical talent ready to make a real-world impact, this is an opportunity to help shape the future of AI native financial services.

We're a small team (two people + you) and we're moving very quickly!

As our ML engineer, you will:

• Build and deploy ML and LLM-powered applications that deliver actionable financial insights and decision support.

• Work end-to-end across the stack: from prompt design and fine-tuning models, to architecting scalable inference infrastructure and designing evaluation frameworks.

• Rapidly prototype and iterate with product and design to bring new AI-native features to life.

• Ensure enterprise-grade reliability and low latency in real-world, high-stakes financial settings.

• Play a central role in shaping our engineering culture, technical direction, and AI stack.

• We’re open to both seasoned ML engineers and standout graduates — what matters is talent, drive, and a hunger to build at the frontier of AI.

• Strong technical ability in machine learning, NLP, or large language models.

• Hands‑on experience with Python, PyTorch/TensorFlow, Hugging Face, LangChain, or similar frameworks.

• Build robust evaluation frameworks to assess model performance beyond accuracy — focusing on explainability, fairness, and financial reliability.

• Develop guardrails and fail‑safes to ensure AI outputs are trustworthy in high‑stakes financial contexts.

• Work on model interpretability and explainability, making sure SMEs can understand the “why” behind the insights.

• High agency, ownership and curiosity: comfortable working in ambiguous, fast‑moving environments.

• Experience shipping LLM applications in production.

• Contributions to ML/AI projects and/or a portfolio of ML projects you’ve worked on.

• Achievements in competitive programming, STEM olympiads, or other indicators of exceptional technical ability.

• Peer‑reviewed publications.

Please note: This is a 12 month fixed term role

At Allica Bank we want to ensure our employees have the right tools and environment in which to succeed in their role and in support of our customers.

Our employees are at the heart of everything we do, so our benefits are designed with you in mind:

• 
  
• Full onboarding support and continued development opportunities
  
• Options for flexible working
  
• Regular social activities
  
• Pension contributions
  
• Discretionary bonus scheme
  
• Private health cover
  
• Life assurance
  
• Family friendly policies including enhanced Maternity & Paternity leave
  

Don’t worry if you don’t have all the skills or requirements listed on the job description. If you think you’ll be a good fit, we’d still love to hear from you!

We know the ‘9-to-5’ isn’t right for everyone. That’s why Allica Bank is fully committed to flexible and hybrid working. Please let us know what is best for you and, if we can, we will do our best to accommodate.

We’re a diverse bunch here at Allica, with all kinds of experiences, backgrounds and lifestyles. Our openness and differences make us stronger, and we want everybody to feel comfortable bringing as much of themselves to work with them as they like.