Senior ML Engineer

inDrive

inDrive

Software Engineering, Data Science
Limassol, Cyprus · United Arab Emirates
Posted on Apr 24, 2025

Senior ML Engineer

, Limassol · · ·

This role focuses on designing and scaling end-to-end machine learning systems that power real-world applications. Ideal for experienced engineers who enjoy solving complex problems with data and collaborating across product and engineering teams.

Responsibilities

  • Design, build, and deploy machine learning models in production.
  • Work with large-scale structured and unstructured datasets: collection, cleaning, preprocessing.
  • Develop end-to-end ML pipelines: feature engineering, training, evaluation, inference.
  • Collaborate closely with software engineers, data analysts, and product managers.
  • Evaluate different approaches, drive architectural decisions, and design A/B experiments.
  • Monitor and maintain ML systems post-deployment: model drift, retraining, performance metrics.

Qualifications

  • 3 to 5+ years of experience in Machine Learning, Data Science, or ML Engineering.
  • Strong Python skills and hands-on experience with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow).
  • Experience with production-grade ML systems: MLOps, CI/CD, Docker, monitoring.
  • Solid understanding of ML algorithms, model evaluation, and statistical principles.
  • Familiarity with data storage systems (SQL, NoSQL, Data Lakes, S3, BigQuery).
  • Proven track record of deploying and maintaining ML systems in production.
  • Strong communication skills and experience in cross-functional teams.
  • Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Data Science, or a related field.

Conditions & Benefits

  • Stable salary, official employment.
  • Health insurance.
  • Hybrid work mode and flexible schedule.
  • Relocation package offered for candidates from other regions.
  • Access to professional counseling services including psychological, financial, and legal support.
  • Discount club membership.
  • Diverse internal training programs.
  • Partially or fully paid additional training courses.
  • All necessary work equipment.