Machine Learning Engineer Undefined

Machine Learning Engineer :

– The hiring manager is NOT looking for a Data Scientist !

– ML Engineer will join Data Science Innovation (DSI) team and work on developing and implementing universal forecasting models, focusing on ML forecasting techniques using Python and Hadoop.

– DSI application is a unique, ML-driven platform that incorporates over 100 financial metrics to create a Universal Forecasting Model. The application features a Marketplace concept UI with Subscriber/Contributor functionality for enhanced personalization and extensibility across the enterprise.

– Collaborate with Data Scientists in an Agile SDLC environment to bring ML models into production

– The ideal candidate ( MLOps ) will have a strong background in developing and implementing ML models in a production environment. They should be comfortable working with DevOps tools and be able to effectively test ML models to determine the success of their output.

Qualifications – every bullet point below is a MUST HAVE :

– Experience as an ML engineer working on universal forecasting models : ARIMA (AutoRegressive Integrated Moving Average), Seasonal Naive, FB Prophet ( Facebook Prophet ) open-source library for forecasting time series data

– Gluon open-source deep learning library ( might consider some alternatives like Apache MXNet, or experience with PyTorch – TensorFlow – CNTK – Theano – Keras – Caffe2 )

– Hadoop ( HDFS, MapReduce )

– Python

– Other skills : Linux, OpenShift (Kubernetes container platform) and databases like Oracle, MS SQL Server, MongoDB

Please send me your details (resume, work authorization status, current location, availability and compensation expectations) directly to: for an immediate consideration. Make sure to include both the job title and location of the job if you email me directly.

PNC Beeline VMS# 134285-1