Basic Qualifications
•    Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science or Computer Information Systems from an accredited institution
•    Employees must be legally authorized to work in the United States.  Verification of employment eligibility will be required at the time of hire.  Visa sponsorship is not available for this position.
•    This position is subject to the Internal Traffic in Arms Regulations (ITAR) which requires U.S. person status.

Preferred Skills and Qualifications
•    Previous experience in a manufacturing environment highly desired.
•    Previous co-op, internship is preferred.
•    Strong problem-solving skills with an emphasis on manufacturing and process/product engineering.
•    Knowledge of machine vision requirements such as lighting techniques and optics.
•    Knowledge in artificial intelligence inspection with a strong desire to grow and refine skills to expert levels.
•    Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world advantages/drawbacks.
•    Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage etc.)
•    Experience using object-oriented programming languages (C#), relational databases (Microsoft SQL, Oracle).  Experience in HMI suites (Ignition, Wonderware, Labview) would be a plus.  Experience with programmable controllers (Rockwell AB) would be a plus.
•    Experience visualizing/presenting data for stakeholders, customers and end users.
•    Strong written and verbal communication skills for coordinating across teams.
•    Drive to learn and master new analytical technologies and techniques.

 

The Computer AI Engineer position is located at our Howmet Research Center (HRC) in Whitehall, Michigan. 

Primary Responsibilities

•    Working with stakeholders throughout the organization to identify opportunities for leveraging artificial intelligence and machine vision systems to drive business solutions.
•    Developing vision models and data algorithms to increase and optimize manufacturing performance and product yield.  Assess the accuracy and effectiveness of those systems.
•    Coordinating with multiple functional teams to productionize models, monitor their performance and outcomes, and refine based on results.