AIML Engineer - Banking and Financial Services (Northampton, UK)
London
Job Description
GET THE FUTURE YOU WANT!
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible.Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
YOUR ROLE
Capgemini Financial Services is seeking an AI/ML Engineer with Banking and Financial Services domain experience- As an AI/ML Engineer you will be responsible for delivering innovative Conversational AI use cases using AWS ML services, Generative AI, and building custom models where necessary.
- You will work across business areas, managing key analytics products for MI and driving end-to-end (E2E) product lifecycle roadmaps.
- Acting as a bridge between business and technology, you will convert business requirements into functional specifications and enable data-driven insights for machine learning (ML) use cases.
- Develop Conversational AI Solutions: Implement advanced AI and ML-based solutions using AWS ML services and Generative AI to support innovative use cases in Conversational AI.
- Data Enabler for ML Use Cases: Gain a deep understanding of data across source systems to support downstream use cases such as MI, reporting, and insights generation, ensuring data availability and quality for ML initiatives.
- Machine Learning & AI Expertise: Strong hands-on experience with AWS ML services, Generative AI, and custom model development for use cases in Conversational AI and the financial services domain.
- Data Management & Analytics: Proficiency in working with large datasets, ensuring data quality, and enabling data-driven decision-making for machine learning use cases and analytics products.
- Programming & Model Development: Expertise in Python, R, or similar programming languages; experience with ML libraries such as TensorFlow, PyTorch, and scikit-learn.
- Product Lifecycle Management: Experience in managing the end-to-end (E2E) product lifecycle, from concept design to deployment, including both tactical and strategic roadmaps.
- Business & Technology Interface: Ability to translate business requirements into functional and technical specifications, acting as a bridge between business stakeholders and technical teams.
- Cloud Computing & Deployment: Experience in deploying AI/ML models on cloud platforms (especially AWS) and managing infrastructure for scalable solutions.
ABOUT CAPGEMINI
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries.With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
The Group reported 2023 global revenues of €22.5 billion.
Get the future you want | www.capgemini.com.
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