Associate Director, Software Engineering (Model Hosting/Inference Optimisation)

We are seeking an experienced professional to join our team in the role of Associate Director, Software Engineering (Model Hosting/Inference Optimisation).

As a key member of our CTO Platforms (AI Platforms) team, you will design, build, and operate scalable, reliable model hosting platforms for LLMs, embeddings, and STT/TTS across heterogeneous hardware.

Key responsibilities include:

• Designing and implementing scalable model hosting platforms for LLMs, embeddings, and STT/TTS across heterogeneous hardware.
• Driving inference optimisation for latency, throughput, and cost through techniques such as quantisation, KV-cache optimisation, and dynamic/continuous batching.
• Evaluating, integrating, and tailoring inference frameworks (e.g., vLLM, TensorRT-LLM, SGLang) to maximise performance on target hardware.
• Owning inference health and performance monitoring, including latency, throughput, TTFT, memory, availability, and troubleshooting bottlenecks and deployment issues.
• Partnering with hardware teams to apply hardware-specific optimisations and improve resource utilisation.
• Ensuring hosting systems meet production standards for reliability, scalability, security, and high availability.

Requirements include:

• A Bachelor's, Master's, or PhD in ML/NLP/CS/Data Science/Statistics (or related).
• 3 years of experience on AI platforms, covering both model hosting/inference optimisation and fine-tuning pipelines; LLM experience strongly preferred.
• Strong engineering skills in Python and CUDA, with a solid understanding of GPU/CPU architecture and HPC fundamentals.
• Deep inference expertise, including KV-cache, batching, quantisation (INT4/FP8/GPTQ/AWQ), operator optimisation, and framework integration (vLLM, TensorRT-LLM, SGLang).
• End-to-end fine-tuning expertise, including data prep, distributed training, hyperparameter tuning, HF/Accelerate/LoRA/QLoRA, and benchmarking/monitoring/troubleshooting.