At a Glance
- Tasks: Lead the development of cutting-edge ML systems for trading and client behaviour analysis.
- Company: Join a dynamic global FinTech group passionate about AI and technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Exciting chance to shape the future of trading technology.
- Why this job: Be at the forefront of AI innovation in a rapidly growing industry.
- Qualifications: 5+ years in ML engineering with strong GCP experience and Python skills.
The predicted salary is between 80000 - 100000 € per year.
One of the most exciting global FinTech groups are hiring a Lead Machine Learning Engineer with excellent GCP experience. As they continue a major period of growth, both organically and through acquisitions, they are now hiring a Machine Learning Engineer for a greenfield initiative to build a new Production Machine Learning capability.
With a division head who is exceptionally passionate about AI and Technology, the team is heavily investing in a modern tech stack. This is an incredible opportunity for a genuinely enthusiastic Lead ML Engineer to build a critical cornerstone of the group's technology strategy.
Your responsibilities in this role will be:
- Owning the full Production ML Engineering lifecycle including feature stores, training pipelines, model serving and automated retraining - Build on Vertex AI, BigQuery ML, or custom infrastructure as appropriate
- Building Production AI systems for trading intelligence, client behaviour analysis, anomaly detection, and market surveillance
- Forecasting models across trading volumes, revenue, liquidity, and operational metrics using statistical and machine learning techniques
To be successful in applying, you will need:
- 5+ years’ experience building and deploying production machine learning systems in Python, including ownership of feature engineering, training, deployment, retraining, and model lifecycle management (Essential)
- A strong background working with GCP (Essential)
- Excellent experience with time-series data, anomaly detection, classification, clustering, or statistical modelling techniques
- Strong AI literacy with knowledge of frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, langchain and langgraph, as well as experience with MCP, VectorDBs and fine-tuning LLMs
- Prior exposure to trading environments, market data, orderbook analytics, financial time-series (Preferred)
Lead AI Engineer – GCP – FinTech/Trading in London employer: Orbis Group
Join a leading global FinTech group that is at the forefront of innovation in AI and technology. With a strong commitment to employee growth, you will have the opportunity to work on cutting-edge projects in a collaborative and dynamic environment, supported by a passionate leadership team. This role not only offers competitive benefits but also the chance to shape the future of trading intelligence and client behaviour analysis in a rapidly evolving industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer – GCP – FinTech/Trading in London
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech and AI space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to GCP and machine learning. Share your GitHub or any relevant work during interviews to demonstrate your hands-on experience and passion for the field.
✨Tip Number 3
Prepare for technical interviews by brushing up on key concepts in ML and GCP. Practice coding challenges and system design questions that are relevant to production ML systems. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨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 take the initiative to connect directly with us!
We think you need these skills to ace Lead AI Engineer – GCP – FinTech/Trading in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with GCP and production ML systems. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about AI and FinTech, and how your background makes you the perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any cool ML projects, especially in trading or finance, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
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 serious about joining our awesome team!
How to prepare for a job interview at Orbis Group
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description, especially GCP and tools like Vertex AI and BigQuery ML. Brush up on your experience with Python and the specific frameworks listed, as they’ll likely ask you to elaborate on your hands-on experience.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built and deployed production machine learning systems. Highlight your role in the full ML lifecycle, from feature engineering to model serving. Real-world examples will demonstrate your expertise and enthusiasm for the role.
✨Understand the FinTech Landscape
Familiarise yourself with the current trends in FinTech, particularly around trading intelligence and market surveillance. Being able to discuss how your skills can contribute to these areas will show that you’re not just technically proficient but also understand the business context.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s vision for the new Production ML capability and how they plan to integrate AI into their trading strategies. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
