Design, develop, and deploy scalable ML models for personalization and engagement.
Lead end-to-end ML projects from framing to production deployment and monitoring.
Build and optimize data pipelines and feature engineering for large-scale data.
Design experiments and A/B testing to measure model impact.
Collaborate with Product, Engineering, Analytics to translate goals into ML solutions.
Improve reliability, scalability, and performance of production ML services.

🎯 Requirements

8+ years of experience building and deploying ML in production.
Strong foundation in ML algorithms, statistics, and evaluation techniques.
Experience working with large-scale user behavior or content datasets.
Python and ML frameworks PyTorch, TensorFlow, scikit-learn, xgboost.
Experience with distributed data processing and data pipeline technologies.
Strong understanding of experimentation methodologies and performance measurement.

Apply on employer's website

This employer gathers applications via their own applicant tracking system.

You will be redirected to an external application form.

Share job

Meet JobCopilot: Your Personal AI Job Hunter

Automatically Apply to Engineering Jobs. Just set your preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.

Activate JobCopilot