At a Glance
- Tasks: Join our team to develop and optimise cutting-edge AI models and pipelines.
- Company: Chubb, a leader in global analytics with a focus on innovation.
- Benefits: Competitive salary, hybrid work, generous leave, and comprehensive health coverage.
- Other info: Inclusive workplace with strong commitment to diversity and career growth.
- Why this job: Make an impact in AI engineering while working with advanced technologies.
- Qualifications: 5+ years in AI/ML, Python expertise, and fluency in Portuguese and English.
The predicted salary is between 60000 - 80000 £ per year.
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.
Key Responsibilities
- 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.
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. You have a strong commitment 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, or Triton) and an understanding of how to optimize models for GPU deployment.
- Infrastructure: Comfortable working in Linux-based environments and proficient in managing containerized workloads and automated CI/CD pipelines.
- Advanced RAG: Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization.
Preferred Qualifications
- 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).
- MUST be fluent in Portuguese and English.
We offer in return!
- 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
Diversity & Inclusion: At Chubb, we consider our people our chief competitive advantage and as such we treat colleagues, candidates, clients, and business partners with equality, fairness and respect, regardless of their 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 us to make any reasonable adjustments, changes or do anything differently during the recruitment process, please let us know.
AI Engineer (Fluent Portuguese & English) employer: Chubb
Chubb is an excellent employer that fosters a collaborative and innovative work culture, particularly in the dynamic environment of Greater London. Employees benefit from comprehensive professional development opportunities, competitive compensation packages, and a strong commitment to diversity and inclusion. Joining Chubb means being part of a forward-thinking team dedicated to excellence in IT risk and compliance, where your contributions directly impact the organisation's success.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer (Fluent Portuguese & English)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow AI enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and inference pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and coding challenges. Practice explaining your past projects and how you tackled specific problems. Confidence and clarity can make all the difference!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Chubb.
We think you need these skills to ace AI Engineer (Fluent Portuguese & English)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with Python, model training, and any relevant projects that showcase your skills in AI/ML engineering. We want to see how you fit into our team!
Showcase Your Projects:Include specific examples of your work with LLMs, inference optimization, or production-ready systems. We love seeing real-world applications of your skills, so don’t hold back on sharing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you're passionate about AI and how your background makes you a perfect fit for our Global Analytics team. Let us know why you want to join StudySmarter!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy—just follow the prompts!
How to prepare for a job interview at Chubb
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and ML engineering, especially around model training and fine-tuning. Be ready to discuss techniques like LoRA and PEFT, as well as your experience with LLMs. This will show that you’re not just familiar with the concepts but can also apply them in real-world scenarios.
✨Show Off Your Python Skills
Since Python mastery is a must for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain your approach to writing clean, maintainable code. Bring examples of your work that highlight your commitment to coding standards like SOLID and DRY.
✨Talk About Inference Optimization
Be ready to dive into specifics about inference pipelines and how you’ve optimised them in the past. Discuss your experience with high-performance inference servers and any strategies you've implemented to reduce latency. This will show that you understand the importance of performance in AI applications.
✨Prepare for Collaboration Questions
This role involves working closely with business analysts and stakeholders, so expect questions about teamwork and communication. Think of examples where you successfully bridged the gap between technical and commercial requirements. Highlight your ability to collaborate effectively in a cross-functional team.