ML Systems Engineer

Data Science Jobs UK

ML EngineermidEdinburgh, Scotland, UKhybridfulltimeTechnology, Information and InternetPythonLLM fine-tuningRAG/GraphRAGknowledge graphsdistributed systemsperformance engineeringbenchmarking frameworksagentic pipelinesposted 15 Sep
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Job Type Permanent

Work Pattern Full-time

Work Location On-site

Seniority Mid

Posted 28 Aug 2026 (2 weeks ago)

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Job Type Permanent

Work Pattern Full-time

Work Location On-site

Seniority Mid

Posted 28 Aug 2026 (2 weeks ago)

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Machine Learning Engineer, AI Startup (Edinburgh, hybrid, UK-wide considered)

An early-stage AI infrastructure company building a persistent, high-speed knowledge layer for agentic AI, letting thousands of AI agents query a shared knowledge base concurrently. Spinning out of a leading UK university, currently hardware-led and building out its software capability from scratch.

The role

: Own the software-side modelling and benchmarking that proves the system works, working closely with the CTO.

What You’ll Do

  • Own the software model (“digital twin”) used to evaluate system behaviour ahead of dedicated hardware
  • Build agentic AI and GraphRAG workloads showing measurable system-level improvements
  • Build and maintain a benchmark suite (latency, GPU utilisation, token reduction, throughput, cost per query)
  • Design experiments isolating the impact of the semantic memory layer on inference performance
  • Develop enterprise knowledge graph datasets and evaluation methodologies
  • Work with hardware/systems teams to keep software models aligned with hardware capability
  • Generate evidence to support pilots, fundraising, and technical validation

What We’re Looking For

  • Commercial experience in AI systems, retrieval, or AI infrastructure, having shipped production software
  • Hands-on experience with agentic pipelines, LLM fine-tuning, RAG/GraphRAG, or knowledge graphs
  • Strong Python, comfortable across ML, distributed systems, and performance engineering
  • Track record building benchmarks/eval frameworks with real rigour
  • Systems thinker, high agency, comfortable with ambiguity
  • Strong communicator able to translate technical results into clear evidence