Chubb is a world leader in insurance. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, underwriting excellence, superior claims handling expertise and local operations globally.
Key Objectives:
As an AI Engineer, you’ll be working with a global team of AI and machine learning practitioners, software engineers, and business and solution architects to implement state of the art - AI enabled digital solutions to transform the P&C insurance globally. This position offers the opportunity to develop, deploy, and optimize Large Language Models (LLMs) that deliver high quality AI products.
Major Responsibilities:
- Work closely with team of AI engineers to design, build, and serve LLMs to solve complex business challenges using Azure (CPU & GPU environments)
- Researching & implementing state of the art LLM techniques including pre-training, fine-tuning, preference alignment, and deployment while also focusing on prompt engineering and generative AI more broadly
- Heavily focusing on developing novel data sets that enable LLMs to perform new tasks as well as tooling/platforming to collect these samples at scale. You will need strong python data fundamentals coupled with a software mindset for making data processing and collection pipelines repeatable, scalable, and high quality.
- Ensure high quality code that meets business objectives, quality standards and development guidelines.
- Building reusable pipelines, processes, and tools to streamline LLM and generative AI workflows
- Manage project stakeholder expectations and issue communications on progress.
- React to shifting priorities without compromising deadlines and momentum.
- Must have:
- 2 - 5 years’ experience in AI Engineering and/or Machine Learning (ML) with a focus on LLMs, with deep expertise in writing, and reviewing production code in Python.
- Understanding the development lifecycle for LLMs— developing data sets for pre-training, instruction tuning, and preference alignment alongside the modelling techniques for each stage and LLM deployment is as MAJOR plus.
- Multi-disciplinary approach to problem solving, including excellent interpersonal and communication skills (written and verbal). This includes crisply talking about technical solutions while being able to collaborate with business architects effectively.
- Strong knowledge of LLM frameworks and libraries (such as transformers, trl, deepspeed, PyTorch), and exposure to various ML techniques and their practical implementation in production at large scale.
- Experience on distributed, high throughput and low latency architectures
- Strong fundamentals in NLP techniques for text representation, semantic extraction techniques, data structures and modeling.
- Experience building software on top of major container technology (Kubernetes, Docker etc.)
- Nice to have:
- Experience defining system architectures and exploring technical feasibility tradeoffs 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.
At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on job-related qualifications and ability to perform a job. If you require an accommodation during the hiring process or upon hire, please inform Human Resources. If a selected applicant requests accommodation during the recruitment process, Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicant’s accessibility needs.
