At a Glance
- Tasks: Lead the development of cutting-edge ML systems for trading and market 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 shape the future of financial 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 required.
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)
Data & AI Lead - GCP 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. Enjoy a modern tech stack, competitive benefits, and the chance to make a significant impact in building a new Production Machine Learning capability.
StudySmarter Expert Advice🤫
We think this is how you could land Data & AI Lead - GCP
✨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 chats. 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 involving GCP and machine learning. Share your GitHub or any relevant work during interviews to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on key concepts related to ML lifecycle management and GCP tools. Practice coding challenges and system design questions that are relevant to the role. We can help you with resources to get ready!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals who want to make an impact in the AI and FinTech world.
We think you need these skills to ace Data & AI Lead - GCP
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and technology shine through. We want to see that you’re genuinely excited about the opportunity to lead in this space, especially with our focus on building a modern tech stack.
Highlight Relevant Experience:Make sure to clearly outline your experience with GCP and production ML systems. We’re looking for someone who has hands-on experience, so don’t hold back on showcasing your skills in feature engineering, model lifecycle management, and any relevant projects you've worked on.
Tailor Your Application:Take the time to tailor your application to the specific role. Mention how your background aligns with our needs, especially in areas like trading intelligence and anomaly detection. This shows us that you’ve done your homework and are serious about joining our team.
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. Plus, it makes the process smoother for both of us!
How to prepare for a job interview at Orbis Group
✨Know Your Tech Stack
Make sure you’re well-versed in the tools and technologies mentioned in the job description, especially GCP, Vertex AI, and BigQuery ML. Brush up on your experience with Python and the relevant 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 owned the full Production ML lifecycle. Highlight your experience with feature engineering, model serving, and automated retraining. Use concrete examples to demonstrate how your contributions have made a difference in previous roles, especially in trading or FinTech environments.
✨Understand the Business Context
Familiarise yourself with the FinTech industry and the specific challenges it faces. Be ready to discuss how machine learning can enhance trading intelligence, client behaviour analysis, and anomaly detection. Showing that you understand the business implications of your work will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, the tech stack they’re using, and their vision for the future of AI within the company. This not only shows your enthusiasm but also helps you gauge if the company aligns with your career goals and values.
