LLM Engineer – Quantum AI / Model Compression / Deep Learning
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We are currently partnered with a fast-growing deep-tech company operating at the intersection of artificial intelligence and quantum-inspired computing. As part of their expanding AI engineering organization, they are looking to hire LLM Engineers to develop next‑generation large language model technologies focused on efficiency, optimisation, and real‑world deployment.
Key responsibilities
Design and develop novel techniques for compressing and optimising Large Language Models using advanced AI and quantum-inspired approaches
Train, fine‑tune, evaluate, and optimise transformer‑based models for performance, robustness, and efficiency
Conduct benchmarking and rigorous evaluation of model accuracy and inference performance
Develop innovative solutions to improve model scalability, portability, and deployment efficiency
Act as a technical expert within the LLM domain, identifying opportunities for AI‑driven innovation across multiple industries
Collaborate closely with cross‑functional teams to integrate AI models into production‑grade products and platforms
Key requirements
Master’s or PhD in Artificial Intelligence, Computer Science, Data Science, or related field
2–5+ years of experience designing, training, or fine‑tuning deep learning and transformer‑based models
Strong practical experience with Hugging Face ecosystem tools (Transformers, Accelerate, Datasets, etc.)
Strong theoretical understanding of deep learning, neural networks, and modern AI training/inference workflows
Strong understanding of GPU architectures and high‑performance AI workloads xpzdshu
Excellent programming skills in Python with frameworks such as PyTorch
Keywords: LLM / Large Language Models / AI Engineering / Deep Learning / Transformer Models / Hugging Face / PyTorch / NLP / Model Compression / Quantum AI / GPU Computing / AI Optimisation / RAG / TensorRT / vLLM / MLOps / HPC / AWS / Docker / Generative AI
If you are interested in this position, please send a CV.
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