We are seeking a technically exceptional Principal Fintech Machine Learning Engineer to develop production-grade machine-learning systems for financial technology applications.

You will work on advanced data and ML initiatives across areas such as transaction intelligence, fraud prevention, financial risk, customer behaviour, and automated decision systems. The role combines deep engineering expertise with significant technical leadership.

Key Responsibilities

• Design and build scalable machine-learning systems for fintech applications.
• Develop models and intelligent services capable of processing large volumes of transactional and behavioural data.
• Build production ML pipelines covering data preparation, feature engineering, training, deployment, monitoring, and model improvement.
• Collaborate with data scientists, software engineers, product managers, risk specialists, and security teams.
• Develop real-time inference capabilities for transaction and financial decisioning systems.
• Establish engineering standards for model reliability, testing, reproducibility, and observability.
• Optimise ML workloads for performance, scalability, and cost efficiency.
• Investigate model performance and production issues and implement robust solutions.
• Mentor engineers and provide technical direction on machine-learning architecture.
• Contribute to responsible AI practices, model governance, and appropriate documentation.
• Evaluate emerging machine-learning technologies and determine where they can provide measurable value to financial products.

Candidate Profile

• 8+ years of experience in machine learning engineering, software engineering, data science, or a related technical discipline.
• Strong Python and software-engineering skills.
• Deep understanding of machine-learning algorithms, statistical modelling, feature engineering, and model evaluation.
• Experience deploying and operating ML models in production environments.
• Strong knowledge of cloud infrastructure, distributed systems, APIs, databases, and data pipelines.
• Experience with technologies such as Kubernetes, Docker, Kafka, Spark, MLflow, TensorFlow, PyTorch, AWS, Azure, or equivalent platforms.
• Experience applying machine learning within fintech, payments, banking, fraud, risk, or other data-intensive environments is highly desirable.
• Strong architectural thinking and technical leadership capabilities.

What You Will Bring

You should be capable of turning sophisticated machine-learning concepts into dependable production systems. Strong engineering discipline is essential, particularly around model monitoring, data quality, scalability, security, and operational reliability.

The Opportunity

This is an opportunity to work on advanced financial technology where machine learning has a direct impact on transaction intelligence, risk management, automation, and customer outcomes. The role offers significant technical autonomy and a pathway toward broader engineering and AI leadership.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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