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
Please contact Charles Duran at IC Resources.