6 of 6 Qwen Jobs in the UK

velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves - real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs - delivering large cost and latency wins (for example ...

velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves - real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs - delivering large cost and latency wins (for example ...

private models. You will be responsible for tailoring deep learning models to specialized domain tasks. Key Responsibilities Fine-tune open-source models (Llama, Mistral, Qwen) for specific domain functions Optimize model deployment pipelines for low latency and high throughput Build advanced context management and semantic search solutions Implement prompt evaluation ...

model fine-tuning strategy, such as SFT, LoRA/QLoRA, and optimisation approaches Selecting and evaluating base models (e.g. Mistral, Qwen, Phi, Falcon) based on performance, cost, and use case Defining evaluation frameworks and standards to ensure models meet production-grade quality and reliability Building and scaling a suite ...

vector retrieval, function calling, secure tool execution). Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude). Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions. Strong analytical problem-solving, ownership ...

constrained hardware such as Jetson, Android, iPad, Raspberry Pi or microcontrollers. Hands-on with llama.cpp or similar, and evaluating small on-device models (e.g. Qwen, Gemma, MedGemma, custom). Some hardware exposure: anyone doing genuine edge AI tends to have this. Cloud experience (AWS), particularly running LLMs in a cloud ...