✨ About The Role
- The role involves owning end-to-end execution of ML-based targeting products such as smart targeting expansion, keyword targeting, and user lookalikes
- Responsibilities include offline & online experimentation of ML models to improve targeting products and drive advertiser outcomes
- Research, implement, test, and launch new model architectures for retrieval using deep learning techniques like GNNs, transformers, and two tower models
- Collaborate closely with multiple stakeholders across product, engineering, research, and marketing to integrate ML solutions into targeting products
- Work on large-scale data systems, backend services, and product integration to deliver the most relevant audiences to advertisers
âš¡ Requirements
- Experienced machine learning engineer with a strong background in developing and implementing ML systems at scale
- Proficient in Tensorflow/Pytorch and experienced in training, evaluating, testing, and deploying machine learning models
- Skilled in large-scale data processing and pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQuery
- Ability to collaborate effectively with cross-functional teams and stakeholders to productize ML research and improve targeting products
- Strong technical leadership skills with experience in driving technical roadmaps, project execution, and contributing to team vision and strategy