Vacancy
Applied AI Engineer
£85k - 100k per year + Equity
United Kingdom
Permanent -
Full-time
Job Description
Applied AI Engineer | LLMs, Python, PyTorch/JAX | UK Remote
£85,000 to £100,000
UK-wide. Fully remote.
Base salary plus equity, set around you.
You’ve shipped an AI feature. Then real users got hold of it.
The model behaved differently. Latency mattered. Edge cases appeared. The job became less about the demo and more about making the whole thing work reliably.
Why This Opportunity
Our client is building AI-native applications designed to handle conversations, tasks, organisation and workflows with minimal prompting.
The challenge is reliability. Long-running workflows, persistent context and real-world task completion all need to work outside controlled experiments. This role exists to turn model capability into dependable product behaviour.
What You'll Be Doing
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Build and ship AI features end-to-end, from model behaviour through to the user experience.
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Design and iterate on prompts, tools, memory and agent workflows.
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Turn raw model outputs into structured, reliable and predictable behaviours.
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Debug issues across models, orchestration, infrastructure and product.
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Improve latency, cost and production reliability.
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Build lightweight evaluation frameworks around real-world performance.
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Work with product and engineering to turn ambiguous problems into working systems.
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Use production signals to drive measurable improvements to models and systems.
What You'll Bring
Essential:
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Hands-on experience training, fine-tuning or deploying ML models.
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Strong foundations in machine learning and modern neural network architectures.
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Experience taking ML or AI systems into production, beyond experimentation.
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Production-quality Python engineering.
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Experience working with LLMs, model APIs or open models.
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Experience working across model, infrastructure and product layers.
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Experience diagnosing production ML issues and addressing root causes.
Useful:
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PyTorch or JAX.
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LLaMA, Qwen or similar open models.
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vLLM or other inference and serving tooling.
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Vector databases.
You don’t need every Useful box.
Could This Be You
You might currently be an Applied AI Engineer, Machine Learning Engineer, AI Engineer or ML Systems Engineer.
The strongest fit is someone who has already been responsible for getting AI into users’ hands and then making it perform reliably once it is there.
If most of your experience has stayed within research, experimentation or modelling without production ownership, this probably is not the move for you.
Why You'll Enjoy It Here
You’ll work across the whole AI product problem rather than one narrow layer. Our client works with a small team, collective decision-making and significant individual ownership. You’ll be expected to bring structure to ambiguous problems and execute independently.
The package includes base salary plus equity, with no fixed salary bands. It is shaped around the person they hire.
Let's Talk
If you’re building production AI systems and want more ownership of what happens between model capability and real-world behaviour, speak to Xist4.
We’ll ask what you expect to earn in your next role, not what you earn now.
We welcome applications from people of all backgrounds and can support reasonable adjustments throughout the process.