AI Engineer (Fluent in Thai and English) – Global Analytics team in London. This role focuses on the end‑to‑end lifecycle of production‑grade AI, from training and fine‑tuning specialized models to architecting high‑performance inference pipelines. The ideal candidate treats AI as a rigorous engineering discipline, writing maintainable Python code and ensuring that every solution—whether a voice agent or a document processor—is built for reliability, low latency, and global scale.
Key Responsibilities
- Model Training & Fine‑Tuning: Lead the adaptation of Large Language Models (LLMs) for domain‑specific tasks using techniques such as LoRA, QLoRA, and PEFT to balance performance with resource efficiency.
- Inference Optimization: Architect and optimise inference pipelines to minimise TTFT (Time to First Token) and maximise throughput via quantisation, caching strategies, and efficient batching.
- Production Engineering: Build and maintain real‑time AI pipelines using WebSockets and SSE, ensuring seamless low‑latency delivery for voice (ASR/TTS) and text applications.
- Architecture & MLOps: Deploy and orchestrate models within containerised micro‑service architectures (Docker/Kubernetes), ensuring robust monitoring, security, and scalability.
- Collaborative Delivery: Work closely with Business Analysts and internal stakeholders to bridge the gap between commercial requirements and technical implementation.
Qualifications
- Professional Experience: 5+ years in AI/ML engineering with a documented history of moving complex models from research into production.
- Python Mastery: Deep proficiency in Python, committed to clean coding standards (SOLID/DRY), modular design, and comprehensive unit/integration testing.
- Generative AI Deep Dive: Hands‑on experience with LLM training cycles, parameter‑efficient fine‑tuning (PEFT), and sophisticated prompt engineering.
- Inference Stack: Experience with high‑performance inference servers (e.g., vLLM, TGI, Triton) and understanding of GPU deployment optimisation.
- Infrastructure: Comfortable working in Linux‑based environments, managing containerised workloads and automated CI/CD pipelines.
- Advanced RAG: Experience building production‑ready Retrieval‑Augmented Generation systems, including vector database management and semantic search optimisation.
- Preferred Qualifications: Experience in the insurance or financial services sector; deep knowledge of GPU architecture, CUDA, hardware‑level performance optimisation; familiarity with Document Intelligence frameworks (OCR, layout analysis, multimodal extraction).
- MUST be fluent in Thai and English.
Benefits
- Competitive salary & pension scheme
- Discretionary bonus scheme
- 25 days annual leave plus ability to purchase 5 additional days
- Hybrid working options
- Private Medical cover
- Employee Share Purchase Plan
- Life Assurance
- Subsidised gym membership
- Comprehensive Learning & Development offerings
- Employee Assistance programme
Equal Employment Opportunity Statement
We are an ethical and honest company wholly committed to its clients and to mutual trust and respect for employees and partners. We consider our people our chief competitive advantage and treat colleagues, candidates, clients, and business partners with equality, fairness and respect regardless of age, disability, race, religion or belief, gender, sexual orientation, marital status or family circumstances. We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or long‑term condition (for example dyslexia, anxiety, autism, a mobility condition or hearing loss) and need any reasonable adjustments or changes, please let us know.
