MLOps Engineer (LLM/GenAI)

Skip to main content MLOps Engineer (LLM/GenAI) Sheffield, United Kingdom • Birmingham, UK + 1 more Hybrid Job Description Job ID 48236 Work Style Hybrid Worker Brand HSBC Department Technology Job Type Full Time Date Posted 23 June 2026 Apply By 07 July 2026 If you’re looking for a career that will help you stand out, join HSBC, and fulfil your potential - whether you want a career that could take you to the top, or an exciting new direction, we offer opportunities, support and rewards that will take you further. We’re one of the largest banking and financial services organisations in the world, with a network that covers more than 50 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people fulfil their hopes and realise their ambitions. We are seeking a MLOps Engineer (LLM/GenAI) In this fantastic role, you’ll engineer production-grade infrastructure for modern AI: hosting LLMs and speech/embedding models, pushing inference performance on real hardware, and building repeatable fine-tuning pipelines that ship domain-adapted models into production. If you like hard performance problems, platform engineering, and seeing your work used broadly across a global organisation, this role is built for you As an HSBC employee in the UK, you’ll have access to tailored professional development opportunities and a competitive pay and benefits package. This includes private healthcare for all UK-based employees, enhanced maternity and adoption pay and support when you return to work, and a contributory pension scheme with a generous employer contribution. In this role, you will: Design, build, and operate scalable model hosting platforms for LLMs, embeddings, and STT/TTS across heterogeneous hardware Optimise inference for latency, throughput, and cost (e.g., quantisation, KV-cache optimisation, dynamic/continuous batching) Evaluate and integrate inference frameworks (e.g., vLLM, TensorRT-LLM, SGLang) to maximise performance on target hardware Own inference health/performance monitoring (latency, throughput, TTFT, memory, availability) and troubleshoot bottlenecks/deployment issues Build end-to-end fine-tuning pipelines (data prep → distributed training → validation) and integrate fine-tuned models into the hosting/inference stack To be successful in this role you should have the following skills: Extensive experience in building AI platforms covering model hosting/inference optimisation and fine-tuning pipelines (LLM experience strongly preferred) Strong Python and CUDA engineering; solid understanding of GPU/CPU architecture and HPC fundamentals Deep inference optimisation expertise: KV-cache, batching, quantisation (INT4/FP8/GPTQ/AWQ), operator optimisation, framework integration (vLLM/TensorRT-LLM/SGLang) Production hosting experience with Docker/Kubernetes and cloud platforms (AWS/GCP/Azure) End-to-end fine-tuning expertise: data preparation, distributed training, hyperparameter tuning, HF/Accelerate/LoRA/QLoRA, plus benchmarking/monitoring/troubleshooting Opening up a world of opportunity. Being open to different points of view is important for our business and the communities we serve. At HSBC, we’re dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, socio-economic background or age. We are committed to removing barriers and ensuring careers at HSBC are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role. If you have a need that requires accommodations or changes during the recruitment process, please get in touch with our Recruitment Helpdesk via hsbc.recruitment@hsbc.com. Read More Overview Our Teams Students and Graduates Life at hsbc Apply Talent Network View all jobs Useful links Privacy Notice Cookie policy Accessibility