AI Engineer - Production ML for Insurance (Hybrid)

Chubb; Greater London; Hybrid; GBP 90.000 - 140.000; Vollzeit

Benefits dieser Stelle

Hybrid working options

Private Medical cover

Employee Share Purchase Plan

Life Assurance

Subsidised gym membership

Comprehensive Learning & development

Zusammenfassung

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.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

Python

LLM training

PEFT

Prompt engineering

CI/CD

Linux

Tools

Docker

Kubernetes

vLLM

Triton

Vector databases

Semantic search

Jobbeschreibung

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.