Applied AI Engineer

Job Scope

• Partner with product and engineering teams to turn loosely defined problems into working systems.
• Optimise AI features for latency, cost and reliability in production.
• Design, test and refine prompts, tools, memory and agent workflows.
• Build lightweight evaluation frameworks to measure how features perform in real-world use.
• Deliver AI features end to end, from model through system to user experience.
• Troubleshoot issues across the full stack, including model, orchestration, infrastructure and UX.
• Convert raw model outputs into structured, dependable and predictable behaviour.

Requirements

• Able to write clean, production-quality code.
• Hands-on experience training, fine-tuning or deploying machine learning models.
• Strong problem-solving ability in fast-paced settings where requirements are not always clearly defined.
• Solid grounding in machine learning and modern neural network architectures.
• Focus on shipping, iterating and improving continuously.
• Comfortable working across layers, from model to infrastructure to product.

Tech Stack

• Vector databases
• LLMs (e.g. OpenAI-style APIs, LLaMA, Qwen)
• Python
• Inference and serving frameworks (e.g. vLLM)
• PyTorch / JAX

We regret that only shortlisted candidates will be notified.

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