Machine Learning Engineer – Pricing Models

About the role

Kavak, the leading e-commerce platform for buying and selling pre-owned vehicles in Latin America, is expanding into the Middle East and is hiring a Machine Learning Engineer for its UAE team. You will build, run and maintain the ML infrastructure behind Kavak UAE's pricing: automated mapping of market listings to catalog SKUs, a pricing algorithm and other models that improve pricing accuracy, strategy and margin.

Key responsibilities

• Build and maintain the listing-to-SKU mapping engine, including rules, text matching and classifiers with confidence thresholds and human review queues.
• Develop an image-based car identification model (make, model, year, generation and trim) for listings with no usable text.
• Manage the local pricing algorithm, run experiments, improve accuracy and reduce bias, and report results.
• Design backtests, holdout sets and audit samples, and document models, assumptions and results for non-technical stakeholders.
• Productionise models as scheduled pipelines with monitoring, retraining and data quality checks.
• Build data pipelines from the data warehouse, scrapers, the catalog and the backoffice.
• Build supporting models for pricing strategy such as depreciation and km curves, price elasticity, days-to-sell and demand.
• Turn reviewer feedback and manual overrides into training data and rules with expiry dates.
• Work with Pricing, Data, Product and global teams on data access, deployment and priorities.

Required profile

• 3-5 years in ML engineering or applied data science, with at least two models taken to production.
• Background in e-commerce, marketplaces, automotive, fintech or any pricing/valuation domain.
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related field; a Master's in Machine Learning or Data Science is preferred.

Required skills

• Python ML stack: pandas, scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow.
• SQL on BigQuery, Databricks or a similar cloud warehouse.
• Pricing models: regression and quantile regression, prediction intervals.
• Text matching and entity resolution, statistics and evaluation (holdouts, backtests, A/B testing).
• MLOps: Docker, Airflow or similar, MLflow or Weights & Biases, Git on GitLab with CI/CD.
• Nice to have: Google Cloud or AWS machine learning certifications, Arabic language, and experience with computer vision, LLMs, vector search, survival analysis, label tools and FastAPI.