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Falcomm
Verified live 2d ago

ML Software Engineer Intern - AI/CAD Integration

Brief overview

Atlanta, Georgia, USIn-person
Machine learningSoftware developmentModel training and servingDataset automationCode documentationCode reviewResearch and evaluation of ML technologiesCollaboration with engineering teams

Job description

Are you passionate about applying machine learning to transform the future of semiconductor design? At Falcomm, we are on a mission to revolutionize semiconductor technologies by integrating AI-driven solutions into the design and development of our energy-efficient power amplifier products. As a ML Software Engineer Intern in AI/CAD Integration, you will collaborate with our team of experts to develop and deploy AI/ML models that enhance CAD workflows, automate design processes, and accelerate innovation in RFIC design. This role offers a unique opportunity to work at the intersection of software engineering, machine learning, and semiconductor design, contributing directly to tools and methodologies that drive next-generation hardware solutions.

We are seeking an intern who thrives in a fast-paced environment, is eager to tackle complex technical challenges, and is motivated to turn AI research into practical engineering solutions. If you have a strong foundation in machine learning, software development, and a desire to apply these skills to advance semiconductor innovation, we invite you to join us. At Falcomm, your creativity and technical expertise will help shape energy-efficient technologies that set new industry standards.Responsibilities

  • Design and implement code for training/serving ML models in chip design workflows
  • Automate creation of large datasets for training models
  • Integrate ML models into existing chip design software infrastructure
  • Write comprehensive tests and documentation
  • Collaborate with engineers to understand model requirements and deployment needs
  • Participate in code reviews and follow software engineering best practices
  • Research and evaluate new technologies for ML model serving and deployment

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