Senior Machine Learning Engineer at The Execu|Search Group in Seattle, Washington

The Execu|Search Group
Published
August 1, 2020
Location
Seattle, Washington
Job Type

Description

Senior Machine Learning Engineer

Local candidates will only be considered at this timeAn entertainment organization in Washington is currently seeking a new Machine Learning Engineer for a promising position with their growing staff. In this role, the Machine Learning Engineer will be responsible for operationalizing and deploying machine learned models that improve the relevance and discoverability of what customers see when they use the organization's products.

Responsibilities

The Machine Learning Engineer will be responsible for Working with Data Science teams to create machine learned models and building a framework to quickly bring those models and their subsequent iterations into production Bringing models to production and enabling others to do the same Laying the foundation for a seamless pipeline that decreases the cost of launching ML models to increase the throughput of experimentation and experience optimization. Assisting in the prioritization of where we apply models to business problems Staying up to date on industry trends around applied machine learning and how they apply to the company's problem space Qualifications 10+ years of Software Engineering experience with 5+ years of experience with Machine Learning Operations High School Diploma GED Experience working as part of a Software Engineering team Experience building machine learning systems for production applications Hands-on development experience in a programming language like Python, Java, JavaScript, and C++ Ability to use statistical methodologies to ensure we have sufficient statistical power to accurately evaluate results Great interpersonal skills Excellent communication skills (written and verbal) Strong attention to detail Highly organized Desired Skills Associate's andor Bachelor's Degree in Computer Science, Engineering, Mathematics, andor Statistics Experience with machine learningdeep learning frameworkslibraries like AWS SageMaker, TensorFlow, PyTorch, MXNet, or related. Background in handling big data via open-source tools (e.g. Spark, Hadoop) or using 3rd party platforms that can convert data sets into high quality models


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