Automation Lead

Summary

Join Careem, a leading app in the Middle East, and contribute to its AI initiatives. You will build, train, and evaluate machine learning models for various services, working with real-world data and collaborating with cross-functional teams. This hands-on role involves deploying models, running experiments, and improving model monitoring. You will tackle challenges in areas like OCR, dynamic pricing, and fraud detection. The ideal candidate possesses strong ML fundamentals, Python skills, and experience with ML frameworks. This role offers the opportunity to make a significant impact on millions of users.

Requirements

• Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related technical field
• Up to 3 years experience working with machine learning in any form: internships, research, personal projects, Kaggle competitions, or a previous job
• Solid Python skills, especially with libraries like pandas, NumPy, and scikit-learn
• A strong grasp of ML fundamentals like classification, regression, cross-validation, and evaluation metrics
• Familiarity with at least one ML framework such as TensorFlow, PyTorch, or XGBoost
• Clear communication, curiosity, and the ability to work well in a team

Responsibilities

• Build, train, and evaluate machine learning models for key services like ride-hailing, food delivery, and payments
• Work with real-world data and translate it into features, signals, and insights
• Collaborate with operations, engineers, product managers, and analysts to tackle challenges like OCR based partner onboarding, dynamic pricing, route optimization, churn prediction, and fraud detection
• Run experiments, track model performance, and help roll out models into live systems
• Improve the way we serve and monitor machine learning models
• Contribute to a strong team culture of learning, iteration, and accountability

Preferred Qualifications

• Exposure to deep learning techniques in NLP, vision, or recommender systems
• Experience working with large datasets using Spark, Hive, or cloud tools
• Familiarity with model deployment and monitoring workflows (Airflow, MLflow, etc.)
• Interest in solving real operational challenges like logistics, fraud detection, or customer retention
• A GitHub profile or project portfolio that shows what you’ve built

Benefits

• A chance to work on AI problems at regional scale that improve lives and drive real business outcomes
• A smart, motivated team that values learning and practical impact
• Flexibility to work remotely, with strong support for collaboration and ownership