Machine Learning Engineer at KoraPay - Remote

Korapay is a payment infrastructure servicing a wide band of businesses making local and international payments. We are a marketplace for digital financial services across Africa. Our vision, which is at the core of what we do every day, is to create a world void of digital financial barriers across Africa. We are committed to delivering reliable, secure, and easy to use digital financial solutions to every single customer with a guarantee that it is improving their lives.

We are recruiting to fill the position below:

Job Title: Machine Learning Engineer

Location: Nigeria (Remote)
Job type: Full-time
Category: Information Security

About The Role

• We run payments across Africa and are now positioned as a global fiat and stablecoin payment infrastructure. We offer mobile money, virtual bank accounts, and virtual cards for payins and payouts across multiple markets. Our data infrastructure is batch-first (Airflow + a cloud data warehouse) and we use Vertex AI for our MLOps lifecycle. The ML team is high-ownership: you will build models, design systems, ship them, and observe them in production.
• You will work on merchant-facing intelligence: forecasting, anomaly detection, segmentation, as well as automation and product-layer ML. If you want to build practical things that matter in a context that most ML engineers never get near, this is the role.

What You'll Work On

• Design and ship a per-merchant payment volume forecasting system: time-series decomposition, Africa-specific event calendars (salary cycles, MNO maintenance windows, public holidays), quantile regression for uncertainty bounds
• Build and maintain fraud/ anomaly detection across the payment stack (residual-based and model-driven) with tiered alerting logic mapped to merchant risk profiles.
• Own the dynamic merchant segmentation system end-to-end: rule-based and data-driven hybrid, percentile thresholds grounded in EDA, segment-transition features as ML inputs
• Instrument and monitor deployed models: drift detection, retraining triggers, and evaluation pipelines via Vertex AI
• Build automation tooling that sits alongside the core ML work: Airflow DAGs, pipeline scaffolding, and tooling to reduce operational toil
• Contribute to product and strategic thinking.

Requirements
Our Stack:

• Apache Spark and Airflow
• Google Vertex AI
• Python
• SQL
• GCS/BigQuery

What We're Looking For:

• 3+ years as an ML engineer in a production environment
• Strong Python and comfort with Spark for large-scale data processing
• Experience with time-series modelling: decomposition, forecasting, anomaly detection
• Solid grasp of the ML lifecycle as a unified discipline
• Ability to work with batch infrastructure and design for it deliberately
• High ownership mentality: you notice problems and fix them as opposed to waiting to be assigned
• Ability to identify gaps in data-driven business processes and come up with solutions

Strong plus:

• Familiarity with Vertex AI (custom training jobs, model registry, pipelines, monitoring)
• Experience in payments, fintech, or any domain where label quality, distribution shift, and operational constraints are real problems
• Exposure to African market dynamics
• n8n or similar automation/workflow tooling experience

Important:
You will be evaluated less on credentials or certifications and more on the quality of your thinking. In this team, a strong ML engineer:

• Can explain why a design decision was made and what it trades off
• Writes systems that the next person can understand and build on
• Is honest about model limitations, especially in production contexts where overconfidence causes real loss
• Closes the loop between model outputs and business outcomes without needing to be told to.

Benefits

• Health insurance
• Sponsored and tailored training
• Paid parental leave
• Paid time-off
• Flexible work style
• Low-interest loans
• Group Life Insurance
• Access to up to four therapy sessions monthly
• Day off on your birthday 
• Employee interest groups that provide supportive communities within Kora
• Great company culture and the opportunity to work with a highly collaborative team building something great!

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online