Machine Learning Engineer

  • Apex Resources Ltd
  • 22/01/2026
Seasonal Information Technology Telecommunications

Job Description

Apex Resources limited are on the lookout for a Machine Learning Engineer (Agentic AI) in Glasgow for a hybrid role.

A leading Glasgow-based AI firm is building next-generation agentic AI products that automate complex tax and finance workflows for UK accountancy firms and in-house finance teams. The platform leverages large language models and intelligent orchestration to remove repetitive work and free specialists to focus on higher-value advice.

The role

You will join a small, high-calibre engineering team as an AI Developer, working on the core agentic AI platform for tax and finance automation. Day-to-day, you will design, build and ship production-grade features across the AI orchestration, reasoning and integration layers.

Typical work includes:

  • Designing and implementing agentic AI workflows that coordinate LLMs, tools and reasoning engines to handle end-to-end finance and tax processes.
  • Building robust back-end services and APIs to support document ingestion, data extraction, multi-step reasoning and autonomous execution.
  • Working with modern LLM tooling (advanced prompting, retrieval-augmented generation, tool calling, evaluation frameworks) to optimise accuracy, latency and reliability for real client workloads.
  • Collaborating with product managers, domain SMEs (tax and finance) and fellow AI engineers to deliver features from concept through to production.
  • Contributing to code quality, observability and secure engineering practices in a regulated, data-sensitive environment.

Our tech stack

You do not need experience with everything below, but you should be strong in several and able to learn the rest quickly.

  • Languages: Python (core), plus exposure to TypeScript/JavaScript helpful for front-end integrations.
  • AI & data: LLMs (OpenAI/Anthropic-style APIs), vector databases/RAG, agent frameworks, basic MLOps for deploying and monitoring AI systems in production.
  • Orchestration: Workflow engines, event-driven architectures, multi-agent coordination systems.
  • Cloud & infra: Azure or AWS, containerised services (Docker/Kubernetes), CI/CD pipelines and modern DevOps practices.
  • Platform integrations: Connecting agentic AI to third-party tax/finance systems and APIs within customers existing tech stacks.

What we re looking for

Essential:

  • 2+ years post-graduate experience as a Software Engineer / AI Engineer / ML Engineer working on production AI systems.
  • Strong software engineering fundamentals: clean code, testing, version control and debugging in Python or similar.
  • A Master s degree (or above) in Computer Science, Mathematics, AI/ML, Data Science, or a closely related discipline from a top-tier university.
  • Demonstrable experience with applied AI/ML or LLM-based systems (projects, internships, or commercial work), not just academic exposure.
  • Comfort working in a fast-moving, small-team environment where you take ownership from idea through to production release.

Nice to have:

  • Experience building agentic AI systems (tool-calling, multi-step planning, self-improvement loops) or autonomous agents.
  • Knowledge of advanced agentic patterns and concepts like Model Context Protocol or similar orchestration standards.
  • Exposure to financial, tax or accounting data and the nuances of working in regulated or data-sensitive environments.

Why join?

  • Direct impact: Ship agentic AI that immediately removes hours of manual work for tax and finance teams every day.
  • Cutting-edge AI: Work at the forefront of agentic AI and enterprise-grade autonomous systems, delivering beyond proof-of-concepts.
  • High-calibre team: Join experienced AI engineers shaping the future of finance automation with production-grade agentic technology.
  • Growth opportunity: Be part of a scaling AI product business with room to shape technical direction and best practices.

How to apply

Send your CV to Chris at Apex Resources or call on (phone number removed)