AI engineer in insurance

Chubb; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid working options

Private Medical cover

Employee Share Purchase Plan

Life Assurance

Subsidised gym membership

Comprehensive Learning & development

Job summary

Chubb in London is seeking an AI Engineer to join our Global Analytics team. You will own the end-to-end lifecycle of production-grade AI, from model training to high-performance inference pipelines, delivering reliable, low-latency solutions for voice and text applications.

The role emphasizes clean Python code, modular design, and robust testing, with deployment in containerized microservices and modern MLOps practices. Fluent in English and Mandarin/Cantonese is required.

Qualifications

• 5+ years in AI/ML engineering with production deployment track record.
• Strong Python expertise and clean code standards.
• Experience with LLM training and PEFT.
• Experience with high-performance inference servers (vLLM/TGI/Triton).
• Experience building Retrieval-Augmented Generation systems.
• Fluent in Mandarin or Cantonese and English.

Responsibilities

• Lead model training and fine-tuning for domain tasks.
• Design and optimize inference pipelines to reduce TTFT and improve throughput.
• Build real-time AI pipelines using WebSockets and SSE for voice and text apps.
• Deploy models in containerized microservice architectures (Docker/Kubernetes) with monitoring and security.
• Collaborate with business analysts to bridge commercial requirements and technical implementation.

Skills

Python

LLM training

PEFT

Prompt engineering

CI/CD

Linux

Tools

Docker

Kubernetes

vLLM

Triton

Vector databases

Semantic search

Job description

Описание

We are seeking an AI Engineer to join our Global Analytics team in London. This role is focused 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 views AI as a rigorous engineering discipline. Beyond building models, you will be responsible for writing high-quality, 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.

Задачи

• Model Training & Fine-Tuning: Lead the adaptation of Large Language Models (LLMs) for domain-specific tasks using techniques like LoRA, QLoRA, and PEFT to balance performance with resource efficiency.
• Inference Optimization: Architect and optimize inference pipelines to minimize TTFT (Time to First Token) and maximize throughput. This includes implementing quantization, 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 containerized microservice 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.

Требования

• 5+ years in AI/ML engineering with a documented history of moving complex models from research into production.
• Deep proficiency in Python.
• You have a strong commitment to clean coding standards (SOLID/DRY), modular design, and comprehensive unit/integration testing.
• Hands-on experience with LLM training cycles, parameter-efficient fine-tuning (PEFT), and sophisticated prompt engineering.
• Experience with high-performance inference servers (e.g., "vLLM, TGI, or Triton") and an understanding of how to optimize models for GPU deployment.
• Comfortable working in Linux-based environments and proficient in managing containerized workloads and automated CI/CD pipelines.
• Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization.
• MUST be fluent in Mandarin OR Cantonese and English
• Будет плюсом: Experience in the insurance or financial services sector; Deep knowledge of GPU architecture, CUDA, and hardware-level performance optimization; Familiarity with Document Intelligence frameworks (OCR, layout analysis, and multimodal extraction)

Условия

• 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 program.