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- Tasks: Lead the design and execution of AI-driven lending systems that make a real-world impact.
- Company: Join a high-growth fintech company revolutionising lending with cutting-edge AI technology.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Be part of a fast-paced team with excellent career advancement opportunities.
- Why this job: Shape the future of lending with autonomous, ethical AI systems in a dynamic environment.
- Qualifications: Experience leading AI/ML teams in regulated environments and expertise in machine learning.
The predicted salary is between 80000 - 100000 £ per year.
A high-growth, technology-led business is building next-generation, AI-powered lending and decisioning systems from the ground up. This is a foundational leadership role—owning the architecture, strategy, and execution of intelligent lending infrastructure. You’ll operate at the intersection of AI, risk, and product, shaping systems that are autonomous, scalable, and grounded in strong ethical and regulatory principles.
If you’re motivated by building production-grade AI systems that directly impact real-world decision-making, this role offers both ownership and scope.
What You’ll Own- End-to-end design of AI-driven lending and decisioning systems (data → models → decision engines → feedback loops)
- Development of agentic AI frameworks to automate and optimise underwriting, risk, and customer journeys
- Deployment of self-improving systems with continuous learning and real-time adaptation
- Technical vision and roadmap for AI within a regulated, high-stakes environment
- Cross-functional alignment across Product, Engineering, Risk, and Operations
- Leadership and scaling of a high-performing AI/ML team
- Intelligent risk and decisioning engines capable of operating with minimal human intervention
- Scalable data and model pipelines for high-volume, high-accuracy predictions
- Transparent, auditable AI systems aligned with regulatory and ethical standards
- Customer-centric AI experiences that improve speed, accuracy, and trust in lending
- Led AI/ML teams in financial services or similarly regulated environments
- Built or scaled lending, credit, or decisioning platforms
- Deep expertise in machine learning and production AI systems
- Strong understanding of regulatory frameworks and risk management
- Ability to operate at both strategy and execution level
- Comfortable in high-growth, ambiguous environments
- Experience with agent-based systems or LLM-powered workflows
- Exposure to ethical AI and model governance frameworks
- Product or UX sensibility in customer-facing financial tools
- Experience scaling teams in early-stage or fast-growth environments
- Arabic or additional language capabilities
Lead AI/ML Engineer - (Fintech/Lending & Decision Systems) Dubai or Remote in Bolton employer: oryxsearch.io
Contact Detail:
oryxsearch.io Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI/ML Engineer - (Fintech/Lending & Decision Systems) Dubai or Remote in Bolton
✨Tip Number 1
Network like a pro! Reach out to people in the fintech and AI/ML space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to AI and machine learning. This gives potential employers a taste of what you can do beyond the written application.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with cross-functional teams.
✨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, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead AI/ML Engineer - (Fintech/Lending & Decision Systems) Dubai or Remote in Bolton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences that align with the Lead AI/ML Engineer role. Highlight your experience in building AI systems, especially in fintech, and don’t forget to mention any leadership roles you've held.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re passionate about AI in lending and how your background makes you the perfect fit for this role. Be sure to connect your past experiences with what we’re looking for.
Showcase Your Projects: If you’ve worked on relevant projects, whether in previous jobs or personal endeavours, make sure to include them. We love seeing real-world applications of your skills, especially those that demonstrate your ability to build scalable AI systems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at oryxsearch.io
✨Know Your AI Inside Out
Make sure you’re well-versed in the latest AI and ML trends, especially those relevant to fintech. Brush up on your knowledge of lending systems and decision-making frameworks, as this will show your passion and expertise during the interview.
✨Showcase Your Leadership Skills
Since this is a foundational leadership role, be prepared to discuss your experience leading AI/ML teams. Share specific examples of how you've scaled teams or projects in high-growth environments, and highlight your ability to align cross-functional teams.
✨Understand Regulatory Frameworks
Familiarise yourself with the regulatory standards that govern AI in financial services. Be ready to discuss how you’ve navigated these frameworks in past roles, as this will demonstrate your capability to operate in a high-stakes environment.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you’ve faced in building AI systems and how you overcame them. This will help you illustrate your strategic thinking and execution capabilities.