Job Description

AI Engineer


The AI Team at Chubb is looking for a multilingual AI Engineer, to join our fast-paced, high-energy team responsible for delivering bleeding edge solutions leveraging AI. This position offers the opportunity to lead an AI engineering team in delivering high quality AI products.


Major Responsibilities


Work closely with team of data scientists to design, build, and test machine learning models to solve complex business challenges on Azure platform with focus on English and non-English models. Researching & implementing state of the art modeling approaches including but not limited to zero-shot/few-shot learning, embedding techniques, fine-tuning etc. Define individual tasks for the development team and track progress on a regular basis. Ensure high quality code that meets business objectives, quality standards and secure web development guidelines. Building reusable tools to streamline the modeling pipeline and sharing knowledge. Manage project stakeholder expectations and issue communications on progress. React to shifting priorities without compromising deadlines and momentum.

Minimum Requirements


Must have: + 5+ years' experience in Machine Learning (ML), with deep expertise in writing, and reviewing production code in Python.
+ Proficiency in Mandarin and English is essential.
Knowledge of ML frameworks and libraries (such as TensorFlow/Pytorch), and exposure to various ML algorithms and their practical implementation in production at large scale. Experience with designing scalable end-to-end Machine Learning/NLP systems Experience on distributed, high throughput and low latency architecture Understanding of NLP techniques around text cleaning/pre-processing, entity extraction, encoder-decoder architectures, similarity matching etc. Experience building software on top of containerization technology (Kubernetes, Docker etc.), and familiarity with frameworks/tools such as FastAPI, Uvicorn Familiarity with Continuous Integration tools such as Jenkin Nice to have: + Experience defining system architectures and exploring technical feasibility trade-offs is a huge plus.
+ Experience in NLP feature engineering and SoTA modeling techniques, such as transformers (e.g., BERT, GPT) is a huge plus.
+ Familiarity with end-to-end application development using full stack is a plus.
+ Experience in P&C insurance is a plus.