Daryl L.

Develop, test, deploy and maintain industry-leading machine learning models for core recommendation feed ranking that serve billions of users daily.

Machine learning for portfolio management applications.

Managed complete lifecycle of R&D project collaborations including problem formulation, proposal preparation, manpower/resource allocation, milestone/deliverable tracking, and intellectual property capture. Designed and developed end-to-end machine learning pipelines in Python using a variety of approaches such as clustering, multiclass classification, time series analysis, learning-to-rank, collaborative filtering, and deep neural networks.

I worked on machine learning methods for learning to rank with applications in audio, text and image retrieval as well as recommendation systems, with two published first-author papers at ICML and one at RecSys.