Lead AI Inference Engineer: Fully Remote (UK Based)
Six Figure Salary + Package
The client is a major UK financial institution building a new AI Engineering capability to support customer and colleague experiences at significant scale. The opportunity involves real production engineering, complex governance and collaboration across global engineering teams.
Lead engineering of shared model hosting, serving, training and fine-tuning capabilities for approved internally managed and open-source models. Work across GPU infrastructure, Kubernetes, serving frameworks, model packaging, inference optimisation, capacity planning and operational reliability.
What you'll be doing
- Building and operating model hosting, serving and deployment capabilities.
- Developing scalable GPU-backed infrastructure and inference services.
- Improving model latency, throughput and cost through performance optimisation.
- Supporting model onboarding, deployment automation, monitoring and rollback.
- Working closely with ML and AI Engineering teams to bring models into production.
What we're looking for
- Strong Python and production software, platform or ML systems engineering experience.
- Hands-on experience with GPU/ML infrastructure, model serving or inference optimisation.
- Knowledge of Kubernetes, cloud infrastructure and automation, ideally AWS.
- Exposure to technologies such as vLLM, Triton, KServe or similar would be advantageous.
- Experience building reliable, scalable systems with strong engineering standards.
- Inference performance: batching, caching, quantisation, benchmarking and latency