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Machine learning engineer

Glasgow (Glasgow City)
Apex Resources Ltd
Machine learning engineer
£70,000 - £90,000 a year
Posted: 26 January
Offer 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.
NO SPONSORSHIP AVAILABLE FOR THIS ROLE
How to apply
Send your CV to Chris at Apex Resources or call on (phone number removed)

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