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Description
It takes a strong background to qualify for this job. As an applicant, you will explain not just how to build solution or models to answer problems, but how to deploy models. These systems will be responsible for judgement of millions of units per day in a challenging production environment. There is a bit of being like a start-up where youʼll occasionally have to wear multiple hats - sometimes youʼll need to be a technical project manager, other time youʼll need to deep dive into databases, while at other times youʼll need to work with optics improvements to be able to see defects consistently so that you can then drive inspection and ML advancements. You will be required to balance technical requirements while effectively managing collaborations with vendors to maintain schedule and ramp dates.
Minimum Qualifications
2+ yearsʼ experience applying computer or machine vision or machine learning techniques to build models that are deployable into a manufacturing environment Software development skills Knowledge of basic networking concepts and protocols, e.g.: TCP/IP, HTTP, etc. Experience with 2D/3D triangulation laser system and/or CCD inspection system such as Halcon, Keyence, Cognex, and/or Visco Familiar with mechanical metrology system qualification process, such as GRR, Correlation, Stability and Reliability Understanding of optics, image acquisition, software filtering and judgment algorithms. Basic understanding of manufacturing processes (i.e. CNC, modeling, laser welding, etc) Intermediate knowledge of automation including system layout, architecture, and cycle time optimization for optical, motion and mechanical systems Ability to Travel approximately 25-50% of the time B.Sc. in Mechanical Engineering, Computer Science, Systems Design, Electrical Engineering or equivalent experience
Preferred Qualifications
Demonstrated technical skills in Machine or Computer Vision as well Machine Learning (CNNs, object detection) Proficiency with Python, CLI, Linux and Unix shell scripting Experience with cloud computing platforms AWS and deployment tools like docker Experience building Software ML solutions – all the way from inception to production. Proficiency in Python is preferred. Experienced user of machine learning and statistical-analysis libraries, such as Turi Create, PyTorch, Keras, Scikit-learn, SciPy. Ability to explain and present analyses and machine learning concepts to a broad technical audience.
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