Job Title: AI/ML Engineer – Fraud & Risk Analytics
Location: Atlanta/Hybrid (US-based, with flexible remote options)
Employment Type: Full-time
About the Role
We are seeking a driven and curious AI/ML Engineer to join our growing data science and machine learning function. You’ll play a key role in designing, developing, and scaling intelligent systems that help enterprise clients detect risk, prevent fraud, and make data-driven decisions with greater precision.
You’ll be joining a cross-functional team of engineers, data scientists, and domain experts who are passionate about building impactful solutions in high-stakes environments. This is an opportunity to work on meaningful real-world problems using large-scale transactional datasets and the latest advancements in ML and statistical modelling.
What You’ll Do
- Build and deploy machine learning models that detect patterns of fraud, anomalies, and operational risk in high-volume financial datasets
- Collaborate closely with data science, product, and engineering teams to define problem statements and identify opportunities for automation and intelligent insights
- Develop, test, and maintain scalable ML pipelines in production environments
- Conduct exploratory data analysis and feature engineering to improve model performance and business interpretability
- Monitor and improve model accuracy, drift, and operational reliability over time
- Contribute to research and experimentation on novel methods in supervised, semi-supervised, and unsupervised learning
- Help define technical direction and best practices across the ML lifecycle
What We’re Looking For
- 4+ years of experience in a hands-on ML/AI or data science engineering role, ideally with experience in the fraud, risk, or financial analytics domain
- Strong knowledge of ML techniques including classification, clustering, anomaly detection, and time series modelling
- Proficiency in Python and libraries such as scikit-learn, XGBoost, TensorFlow/PyTorch, pandas, and NumPy
- Solid experience building and maintaining production-grade ML systems and pipelines (preferably with DataBricks)
- Strong SQL skills and comfort working with large-scale datasets
- Experience translating business problems into data science use cases with measurable impact
- Bonus points for familiarity with graph analytics, Bayesian methods, or explainable AI approaches
Why Join?
This is your chance to help shape the future of enterprise risk intelligence. You’ll be joining a mission-driven, innovation-focused company with an established track record in automating oversight and compliance for large organisations. You’ll work alongside smart, humble teammates in a culture that values curiosity, initiative, and continuous improvement.
