ML Engineer - Real-Time Personalization & Recommendations

BGTS International; Fatih; On-site; TRY 380,000 - 660,000; Full time

Job summary

BGTS is seeking a Machine Learning Engineer to help build intelligent content recommendation experiences. You will work on recommendation systems, real-time personalization, and ML models that help users discover relevant content.

The role involves collaborating with software engineers to deploy ML in scalable production environments and to design robust A/B tests for continuous improvement.

Qualifications

• Bachelor's or Master's in Computer Science, ML, Data Science, Math or Statistics or equivalent practical experience.
• Proficient in Python; Scala experience is a plus.
• Hands-on with TensorFlow, PyTorch or scikit-learn.
• Familiar with Spark and big data processing.
• Solid software development practices and Git version control.
• Strong analytical and problem-solving abilities.

Responsibilities

• Design, develop, and optimize recommendation systems.
• Build real-time personalization and ML models for content discovery.
• Leverage multi-modal signals (vision, NLP, speech) for content understanding.
• Design and evaluate A/B tests to measure algorithm effectiveness.
• Develop personalization strategies using user segmentation and context.
• Build predictive models for engagement, dwell time, and completion probability.
• Monitor and maintain ML models in production.
• Collaborate with software engineers to integrate ML solutions.

Skills

Python programming

Scala programming

Big data processing

ML model deployment

Analytical skills

Problem solving

Education

Bachelor's degree in Computer Science/Data Science/Math/Statistics

Master's degree in CS/ML/Data Science

Tools

TensorFlow

PyTorch

scikit-learn

Apache Spark

Git

Cloud platforms (AWS/GCP/Azure)

Job description

BGTS is seeking a Machine Learning Engineer to help build intelligent content recommendation experiences. You will work on recommendation systems, real-time personalization, and ML models that help users discover relevant content.

The role involves collaborating with software engineers to deploy ML in scalable production environments and to design robust A/B tests for continuous improvement.