Role Description

• Design and build end-to-end ML pipelines covering data, model training, evaluation, inference and production deployment.
• Fine-tune and optimise LLMs using techniques such as LoRA, QLoRA, SFT, DPO and model distillation.
• Develop scalable inference infrastructure with a focus on performance, GPU optimisation, latency and reliability.
• Build high-quality data pipelines and evaluation frameworks to continuously improve model performance.
• Collaborate closely with AI researchers and software engineers to deliver production-ready AI solutions.
• Drive continuous improvements through rapid experimentation and real-world product feedback.
• As a Principal / Technical Lead, you will lead technical architecture, mentor engineering teams and shape the long-term AI platform strategy.

Requirement

• Minimum 4 years of relevant experiences required. Proven technical leadership experience will be consider for Principal or Technical Lead roles.
• Strong experience in Deep Learning, Transformer architectures and Large Language Models (LLMs).
• Hands-on experience training, fine-tuning or deploying large-scale ML models in production.
• Proficiency with PyTorch, JAX or similar ML frameworks.
• Experience with distributed training or inference technologies such as DeepSpeed, FSDP, Megatron, Ray or ZeRO.
• Strong software engineering fundamentals with experience building scalable, production-grade systems.
• Experience in GPU optimisation, quantisation and high-performance inference is highly advantageous.