HSBC Global Services Limited
MLOps Engineer (LLM/GenAI)
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MLOps Engineer (LLM/GenAI)
MLOps Engineer (LLM/GenAI) – HSBC
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 covering over 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.
About the Role
We are seeking an MLOps Engineer (LLM/GenAI) for this fantastic role, where you’ll engineer production-grade infrastructure for modern AI:
- Hosting LLMs and speech/embedding models
- Pushing inference performance on real hardware
- Building repeatable fine-tuning pipelines to ship domain-adapted models into production
If you enjoy tackling hard performance problems, platform engineering, and seeing your work widely used 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 along with a competitive pay and benefits package, including:
- Private healthcare for all UK-based employees
- Enhanced maternity and adoption pay, plus support when you return to work
- A contributory pension scheme with a generous employer contribution
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Key Responsibilities
- Design, build, and operate scalable model hosting platforms for LLMs, embeddings, and speech-to-text (STT)/text-to-speech (TTS) across heterogeneous hardware
- Optimise inference for latency, throughput, and cost (e.g., quantisation (INT4, FP8, GPTQ, AWQ), 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, time to first token (TTFT), memory, availability) and troubleshoot bottlenecks/deployment issues
- Build end-to-end fine-tuning pipelines (data preparation → distributed training → validation) and integrate fine-tuned models into the hosting/inference stack
Requirements
To be successful in this role, you should have the following skills:
- Extensive experience in building AI platforms, covering:
- Model hosting and inference optimisation
- Fine-tuning pipelines (with LLM experience strongly preferred)
- Strong Python and CUDA engineering skills, with a solid understanding of:
- GPU/CPU architecture
- High-performance computing (HPC) fundamentals
- Deep expertise in inference optimisation, including:
- KV-cache optimisation
- Batching strategies
- Quantisation techniques (INT4, FP8, GPTQ, AWQ)
- Operator optimisation
- Framework integration (vLLM, TensorRT-LLM, SGLang)
- Production hosting experience with:
- Containerisation (Docker)
- Orchestration (Kubernetes)
- Cloud platforms (AWS, GCP, Azure)
- End-to-end fine-tuning expertise, including:
- Data preparation
- Distributed training
- Hyperparameter tuning
- Low-rank adaptation techniques (HF, Accelerate, LoRA, QLoRA)
- Benchmarking, monitoring, and troubleshooting
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Commitment to Diversity & Inclusion
HSBC is committed to creating diverse and inclusive workplaces.
No matter their gender, ethnicity, disability, religion, sexual orientation, socio-economic background, or age, everyone deserves equal opportunities. 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 require accommodations during the recruitment process, please contact our Recruitment Helpdesk at: hsbc.recruitment@hsbc.com.
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