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- Tasks: Lead an AI engineering team to deliver cutting-edge AI solutions and tackle complex challenges.
- Company: Join Chubb, a dynamic company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact in AI while working with a passionate, multilingual team.
- Qualifications: 5+ years in Machine Learning, fluent in Mandarin and English, strong Python skills.
- Other info: Exciting projects with excellent career advancement opportunities in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
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 a team of data scientists to design, build, and test machine learning models to solve complex business challenges on the Azure platform with a focus on English and non-English models.
- Research and implement 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.
- Build reusable tools to streamline the modeling pipeline and share knowledge.
- Manage project stakeholder expectations and communicate progress.
- React to shifting priorities without compromising deadlines and momentum.
Qualifications
- 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 Jenkins.
- 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.
AI Engineer employer: Chubb Ltd.
Contact Detail:
Chubb Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those at Chubb or similar companies. Use LinkedIn to connect and engage with them; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving NLP and Python. 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 your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as communication is key in a fast-paced team environment like Chubb's.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with machine learning, Python, and any relevant projects you've worked on. We want to see how your skills match up with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your multilingual skills can benefit our team. Keep it engaging and personal – we love getting to know our applicants!
Showcase Your Projects: If you've worked on any cool AI projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see your hands-on experience and creativity in action.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, it shows you’re serious about joining our fast-paced, high-energy team!
How to prepare for a job interview at Chubb Ltd.
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of machine learning frameworks like TensorFlow and PyTorch. Be ready to discuss your experience with Python and how you've implemented various ML algorithms in production. They’ll want to see that you can not only talk the talk but also walk the walk!
✨Showcase Your Multilingual Skills
Since proficiency in Mandarin and English is essential, be prepared to demonstrate your language skills during the interview. You might be asked to explain complex concepts in both languages, so practice articulating your thoughts clearly in both.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities, especially around designing scalable ML systems or managing project stakeholder expectations. Think of specific examples from your past experiences where you successfully tackled similar challenges.
✨Highlight Your Team Leadership Experience
As this role involves leading an AI engineering team, be ready to discuss your leadership style and how you’ve defined tasks and tracked progress in previous projects. Share examples of how you’ve motivated your team and ensured high-quality outputs.