Machine Learning Engineer at CityOfNewYork

The Fire Department of the City of New York (FDNY) is the largest Fire Department in the United States and universally is recognized as the world's busiest and most highly skilled emergency response agency. The Department's main goal is to provide fire protection, emergency medical care, and other critical public safety services to residents and visitors in the five boroughs. FDNY members are sworn to serve and protect life and property and the Department works to continually educate the public in fire, life safety and disaster preparedness, along with enforcing public safety codes. Since its inception in 1865, FDNY has helped lead efforts to make New York the safest big city in the nation. This accomplishment requires a steadfast and daily commitment to maintaining the Department's core values. Reporting to the Deputy Director of Industrial Engineering, the Machine Learning Engineer will play a key role in our mission to optimize the Fire Department's emergency responses and other processes. The ideal candidate will leverage a wide variety of data analysis techniques to analyze departmental data. This includes utilizing casual inference techniques (such as BART, BCF, DiD, Double ML, etc.) to evaluate the effects of pilots, and time series forecasting (LSTM, SARIMAX, VARMAX, Prophet, etc.) to predict future demand for resources. The ideal candidate will also leverage advanced deep learning architectures, including transformers, to develop and deploy data-driven solutions. The ideal candidate should be experienced in using tools such as MLFlow and Comet to track experiments, as well as being experienced in deploying and monitoring models. The ideal candidate will be experienced in building robust pipelines and systems. This role demands a strong technical background and a pragmatic approach, focusing on creating and implementing models that deliver a quantifiable impact. The ideal candidate will collaborate closely with various technical and operational teams, including GIS, Data Quality, Strategic Initiatives, and IT, to ensure a seamless transition from concept to practice. CITY RESEARCH SCIENTIST - 21744