About Us

Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.

Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.

Your Role

We are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.

You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.

Your Responsibilities

Model Deployment & Scaling

• Productionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architectures
• Design low-latency, high-availability APIs and pipelines for real-time model inference.
• Implement batch scoring systems for periodic risk assessments.=

MLOps & Infrastructure

• Build and maintain CI/CD pipelines for model deployment and monitoring.
• Set up automated feature engineering pipelines, leveraging feature stores.
• Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.

Model Monitoring & Maintenance

• Implement real-time and batch monitoring for data drift, concept drift, and model performance.
• Build automated retraining workflows and model rollback mechanisms.

Collaboration with Risk DS

• Work closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.
• Advise DS on efficient model architectures for operational environments.
• Optimize feature computation for speed and scalability.

System Design & Integration

• Integrate models with credit underwriting, fraud detection, collections, and merchant risk systems.
• Collaborate with backend engineering to align on API contracts and system interfaces.

Your Expertise

• 6+ years of experience as an MLE, ML Engineer, Mlops Developer.
• Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).
• Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).
• Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).
• Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).
• Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).
• Proven track record of deploying and maintaining ML models in production at scale.
• Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).

All qualified individuals are encouraged to apply.

The role

As a Senior Python Developer, you will play a crucial role in developing and maintaining infrastructure and data processing services that complement our C++ trading core. This is a Dubai-based role (we're happy to cover the relocation). 

Responsibilities

• Develop and maintain Python-based infrastructure and data processing services.
• Collaborate with C++ developers to ensure seamless integration and optimal performance.

Required Skills & Qualifications

• Strong proficiency in Python with experience in developing infrastructure and data processing services.
• Ability to write clean, efficient, and well-structured code.
• Exceptional problem-solving skills and meticulous attention to detail.
• Strong prioritisation skills.
• Knowledge of financial markets and trading principles.
• Familiarity with Apache Kafka.
• Experience with SQL databases, especially PostgreSQL.
• Solid understanding of Linux systems, including docker and containerisation.
• Experience with Django, Python Asyncio, Redis.
• Experience with setting up CI pipelines for Python projects.

Other Technologies we Use

Experience with any of the following technologies is considered a significant bonus:

• FastAPI
• Pydantic
• Clickhouse
• Docker
• Grafana
• Prometheus
• Ansible
• Kubernetes
• Terraform
• Grafana
• Gitlab

What we offer

• Flexible working hours and a healthy work-life balance.
• Remote-first team.
• The opportunity to work in a thriving, multicultural, fun environment in one of the world’s fastest-growing industries.
• Corporate workations: we regularly go on corporate trips to unique locations all over the world to work, explore the local culture, and get to know each other better.