Machine Learning Engineer

  • location: Raleigh, NC
  • type: Contract
  • salary: $70 - $80 per hour
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job description

Machine Learning Engineer

job summary:
Title: Machine Learning Engineer (software engineer/programmer)

Location: Raleigh, NC, 27603

Duration: Projected Start Date Jul 22, 2019

Projected End Date Jul 01, 2020 with possibility of extension

Shift: M-F; 9-5 (40 hrs)

For immediate consideration, please contact jomarie.mercado@randstadusa.com

 
location: Raleigh, North Carolina
job type: Contract
salary: $70 - 80 per hour
work hours: 8am to 5pm
education: Bachelors
 
responsibilities:
Summary

Our client is an innovative deep-learning vision processing startup, developing ground breaking products for the rapidly expanding machine learning market. Based on our proprietary Graph Streaming Processor (GSP) custom SOCs, we are building a range of computing platforms. With our focus on ultra-power-efficient edge computing, our comprehensive deep-learning systems (hardware + software) are being adopted in a range of industries from automotive to consumer.

 
qualifications:
Essential Duties and Responsibilities

· Lead design and development of engineering tools for non-coding ML users

· Write, test, and document robust hands-on code with C/C++ and Python

· Collaborate closely with a team of AI experts to solve problems in computer vision, visualization of ML results, and user - ML system interaction

Stay informed about developments in AI and utilize state-of-the-art technology as it emerges

Knowledge, Skills and Experience:

M.S./Ph.D. in relevant field or equivalent experience

3+ years of solid experience designing, training, and implementing autoencoders and/or GANs

Strong programming skills in Python and/or C++

Use of good programming practices including writing, testing, and documenting robust and maintainable code

Knowledge of multiple deep learning frameworks such as PyTorch, Caffe, and TensorFlow

Solid understanding of computer vision fundamentals

Proficiency with computer vision toolkits such as OpenVX is a plus

Broad understanding of Machine Learning across multiple domains, algorithms and applications

Staying current with research on GANs and the latest developments in the AI area, broadly taken.

Proven experience solving problems using deep neural networks, preferably in the field of computer vision

Projects demonstrating your skill set, including published papers, starred Github repositories, or Kaggle achievements

Excellent communication skills and a team mentality

Experience with Agile software development methodology is a plus

 
skills: Essential Duties and Responsibilities

· Lead design and development of engineering tools for non-coding ML users

· Write, test, and document robust hands-on code with C/C++ and Python

· Collaborate closely with a team of AI experts to solve problems in computer vision, visualization of ML results, and user - ML system interaction

Stay informed about developments in AI and utilize state-of-the-art technology as it emerges

Knowledge, Skills and Experience:

M.S./Ph.D. in relevant field or equivalent experience

3+ years of solid experience designing, training, and implementing autoencoders and/or GANs

Strong programming skills in Python and/or C++

Use of good programming practices including writing, testing, and documenting robust and maintainable code

Knowledge of multiple deep learning frameworks such as PyTorch, Caffe, and TensorFlow

Solid understanding of computer vision fundamentals

Proficiency with computer vision toolkits such as OpenVX is a plus

Broad understanding of Machine Learning across multiple domains, algorithms and applications

Staying current with research on GANs and the latest developments in the AI area, broadly taken.

Proven experience solving problems using deep neural networks, preferably in the field of computer vision

Projects demonstrating your skill set, including published papers, starred Github repositories, or Kaggle achievements

Excellent communication skills and a team mentality

Experience with Agile software development methodology is a plus


Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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