National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Principal Engineer

Lime Street
1 week ago
Create job alert

A leading global insurance business is seeking a seasoned AI Leader capable of scaling AI capabilities to transform business models. This pivotal role will oversee a dynamic team responsible for the conception and execution of AI, ML, NLP, and Generative AI solutions, aimed at influencing business outcomes. Your expertise will be used to harness cutting-edge AI capabilities, multiple internal and external data sources to create new AI enabled business models and help businesses improve, profitability, sales, customer experience and operational efficiency.

Key Responsibilities

Your core responsibilities will be to drive AI based solutions, heading all stages of analytics initiatives, recommending, and implementing apt AI and computational methodologies, working with domain experts and business leads. You will lead a team of Machine Learning engineers, producing trail-blazing techniques in deep learning, NLP, and Generative AI.

Qualifications

Essential Skills/Experience

  • 10+ years of experience leading an AI team with hands-on implementation experience with a positive impact to business.

  • Deep understanding of Generative AI, Large Language Models, NLP, deep learning models and model implementation is a must.

  • Top-notch problem-solving skills, quick adaptability, and excellent communication are key.

  • You are expected to have a minimum of 10 years leading a team of ML Engineers, Data Scientists, developing deep learning models, with a solid understanding of recent Generative AI techniques. Familiarity with the P&C industry is preferred.

    Education

  • A PhD or Master’s degree in a field such as Computer Science, Computational Science, Statistics or related fields preferred

  • Relavant Insurance experience

Related Jobs

View all jobs

Principal Engineer

Data Engineer

Principal Data Engineer

Principal Data Engineer, Consulting

Principal Data Engineer, Consulting

Principal Data Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.