At a Glance
- Tasks: Own software modelling for AI systems and benchmark performance metrics.
- Company: Exciting AI startup with a focus on innovative technology and collaboration.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic startup environment with potential for significant impact.
- Why this job: Join a pioneering team and shape the future of AI technology.
- Qualifications: Experience in AI systems and strong Python skills required.
The predicted salary is between 72000 - 88000 £ per year.
An early-stage AI infrastructure company is building a persistent, high-speed knowledge layer for agentic AI, allowing thousands of AI agents to query a shared knowledge base concurrently. The company is spinning out of a leading UK university and is currently hardware-led while building out its software capability from scratch.
The role involves owning 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 skills, comfortable across ML, distributed systems, and performance engineering.
- Track record building benchmarks/evaluation 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.
ML Systems Engineer in Edinburgh employer: Intellectual Capital Resources
Join an innovative AI startup in Edinburgh that is at the forefront of building a high-speed knowledge layer for agentic AI. With a strong emphasis on collaboration and growth, this company offers a dynamic work culture where your contributions directly impact the development of cutting-edge technology. Employees benefit from flexible hybrid working arrangements, opportunities for professional development, and the chance to work alongside leading experts in the field, making it an exciting place for those looking to advance their careers in AI.
Contact Details:
Intellectual Capital Resources Recruitment Team
