Senior ML Engineer

Aveni is redefining how financial institutions use AI. We build real, production-ready agentic systems that reshape how banks, advisers and financial services firms operate, replacing fragmented processes with intelligent, end-to-end workflows. We have been recognised as Fintech of the Year for two consecutive years and awarded Best Specialist Technology Service at the Professional Adviser Awards 2025.

Backed by leading investors including Puma Private Equity, and commercially supported by Lloyds Banking Group and Nationwide Building Society, we previously completed one of Scotland’s largest Series A rounds. Since then, we’ve continued to grow rapidly as adoption of AI in financial services accelerates, and we’re now scaling our team to meet that demand.

We’re looking for a Senior ML Engineer (FinLLM / NLP) to help drive the next generation of AI systems powering financial services. This role focuses on developing, fine-tuning and deploying advanced language models that operate at production scale within highly regulated environments.

You’ll work alongside our NLP team, software engineers, and product leaders to build cutting-edge solutions that transform how financial organisations use AI. This is a hands-on role where you’ll shape both the technical direction and practical deployment of large language models and NLP systems within our platform.

• Build and optimise LLM-powered systems

• Architect, fine-tune and optimise machine learning models including LLMs and classical ML approaches

• Experiment with modern architectures such as Transformers and Mixture-of-Experts

• Apply efficient training and fine-tuning techniques including LoRA and parameter-efficient methods

• Develop robust evaluation approaches to measure model quality and reliability

• Develop scalable AI systems

• Build and deploy production-grade NLP pipelines and services

• Ensure models operate efficiently with low latency and high availability

• Integrate models into scalable cloud infrastructure and real-world applications

• Data strategy and model training

• Lead the acquisition, processing and governance of large structured and unstructured datasets

• Apply exploratory data analysis and validation techniques to improve training pipelines

• Ensure data privacy and governance standards suitable for financial services

• Engineering best practices

• Contribute to Dev Ops and MLOps pipelines

• Implement robust version control, testing and CI/CD workflows

• Support reliable deployment and monitoring of models in production environments

• Technical leadership

• Mentor engineers and contribute to the technical growth of the team

• Work closely with product, engineering and data teams to deliver AI solutions

• Stay at the forefront of AI and NLP research, applying new approaches where they add value

Essential experience

• Significant experience building, training and deploying machine learning models

• Strong Python skills with experience using Num Py, Pandas, Sci Py and modern ML frameworks such as PyTorch or Tensor Flow

• Experience working with large-scale unstructured data

• Experience building and deploying production-ready NLP systems

• Familiarity with API integrations and data acquisition pipelines

• Experience implementing software engineering best practices including Git and agile development

• Experience working with cloud environments (preferably AWS)

Nice to have

• Experience with containerisation technologies such as Docker or Kubernetes

• Experience with frameworks such as vLLM or Ne Mo

• Knowledge of financial services NLP applications

• Experience designing evaluation methodologies for LLM outputs

• Experience building intelligent agents or multi-agent systems

• Skills and mindset

• Strong analytical problem-solving skills

• Ability to design scalable,…