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This challenging role will require someone who deeply understands and can architect algorithms and build systems and teams that advance the application of artificial intelligence and machine learning to the Manufacturing AI market. Practical experience in the use and the building of data analytics tools and components in both cloud and on-premise infrastructure are critical.
What you’ll be doing:
You will be establishing and growing a software team that can architect, analyze, develop and prototype key deep learning and data analytics algorithms and solutions.
Responsible for establishing both cloud and on-premise infrastructure that allows installation, integration, development of various in-house and 3rd party software applications on NVIDIA platforms
Specification and use of various Smart Factory standards that includes IPC-CFX, The Hermes, SECS/GEMS with deployment pipeline and establishing strategies for enabling levels of automation for both on-premise and Cloud IOT platforms
Provide architectural input for distributed applications development that can improve scalability, reliability, and availability for a wide variety of streaming sensor data applications for manufacturing.
Establish processes and tools for compliance, including functional validation, scalability, and alignment to enterprise security.
Work and collaborate with different software, research, and hardware teams across geographies for solving critical problems.
Understand and analyze the interplay of hardware and software architectures on future applications.
Support engagements with customers and their third-party software providers, collaboration with Product Managements, Marketing, and Developer Technology teams.
What we need to see:
MS or PhD in Computer Science, Computer Engineering or Electrical Engineering or related field.
10+ years of semiconductor, electronics, automotive, or other manufacturing industry experience. 8+ years of management experience.
Strong mathematical foundation and extensive experience in Deep Learning, Machine Learning and Computer Vision.
Algorithm development experience for various vision and time-series data analytics.
Knowledge of various industrial processes, workflows, key performance indicators and protocols.
Experience building solutions on Cloud and On-prem backends.
Ability to conceptualize and architect distributed analytics systems.
Experience working with deep learning frameworks like TensorFlow and pyTorch.
Experience in building and managing teams.
Strong communication skills.
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