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, growth opportunities, and a modern tech stack.
- Other info: Exciting chance to work on innovative projects in a collaborative team.
- Why this job: Make a real impact by building critical AI capabilities in a fast-growing environment.
- 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 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
✨Tip Number 1
Network like a pro! Reach out to your connections in the FinTech and AI space. Attend meetups, webinars, or industry events where you can chat with folks who might know about job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to GCP and machine learning. This could be a GitHub repo or a personal website where you demonstrate your expertise in building production ML systems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with feature engineering, model lifecycle management, and how you've tackled challenges in previous roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals like you. Tailor your application to highlight your relevant experience in trading environments and GCP to stand out from the crowd.
We think you need these skills to ace Lead AI Engineer – GCP – FinTech/Trading
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 and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for AI and technology, and explain why you’re excited about this opportunity. Let us know how you can contribute to our greenfield initiative.
Showcase Your Technical Skills:Be specific about your technical expertise in Python, time-series data, and machine learning frameworks. We love seeing concrete examples of how you've used these skills in previous roles, especially in trading environments.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
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 machine learning frameworks like scikit-learn and TensorFlow, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built and deployed production ML systems. Highlight your role in the full lifecycle, from feature engineering to model retraining. Use concrete examples to demonstrate your problem-solving skills and how you’ve tackled challenges in previous roles.
✨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 work can impact client behaviour analysis or anomaly detection will show that you’re not just technically skilled but also understand the business context.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s vision for AI and how they plan to integrate it into their trading strategies. This shows your enthusiasm for the role and helps you gauge if the company culture aligns with your values and career goals.
