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Machine Learning Software Engineer
Job Order #15526
Portland-Vancouver-Beaverton, Oregon - Added Dec 22, 2018

Full Description:

 

Machine Learning Software Engineer

Our largest Beaverton area client is looking for a Machine Learning Engineer to join their team!

Required:

- At least 3-5 years of Software Development experience in Cloud Services using Server-side Javascript(Node.js) or Java or Python or Go.
- Experience with Machine Services capabilities using Amazon ML/Sagemaker or Azure ML Studio or Google ML Engine
- Familiarity with one or more deep learning libraries like TensorFlow/Keras/Caffe2/PyTorch/MXNet
- Experience building ML models with Training Data sets and running ML based Predictions
- Cloud Services development experience preferably with ability to model, specify and consumer REST APIs
- Ability to understand technology deeply and ability to dive in and debug at any level in a software stack
- Familiarity with DevOps model of development and QA within a single team
- Experience with agile development methodologies namely SCRUM and Kan Ban

 

Interested? Send your resume to Ashley at resumes@mbg.com

Reference Job# AKT15526

Mainz Brady Group provides technology staffing solutions to the best known companies in Software Development, Finance, Electronics/Manufacturing, Retail, R&D, Services, Biotechnology, Healthcare and Telecommunications. 

We specialize in Information Technology, Technical Sales and Marketing Staffing on a Contract, Contract to Hire, and Direct Hire basis. 

To see a complete listing of all current openings please visit us at www.mbg.com

 

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“Through the years, Mainz Brady Group has been a strategic partner for Unicru. With a deep understanding of the company, the people, the business and technologies, they have been able to identify who will be most successful in our fast-paced and evolving environment. Additionally, Mainz Brady Group has contributed significantly to building awareness about why Unicru is an employer of choice. By developing and applying complementary business practices, we have very efficiently partnered to find and select the very best.”

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