Motorola Solutions-posted 3 months ago
Intern
Chicago, IL
Computer and Electronic Product Manufacturing

At Motorola Solutions, we believe that everything starts with our people. We're a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that's critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future. The Emerging Technology and ML Ops team is a key part of the Architecture and Technology Solutions group, which incubates and commercializes emerging technology solutions to accelerate innovation, and enables Enterprise applications assets to be unlocked via GenAI, Machine Learning, APIs & Data Science. As a member of this team, you will be part of a rapid development team. You will incubate and develop functional prototypes to showcase capabilities to customers in the AI/ML space. You have a passion for creating world-class web and/or mobile user experiences.

  • Design and implement machine learning models for classification, regression, and other predictive tasks.
  • Develop and prototype generative AI solutions, including Retrieval-Augmented Generation (RAG) and autonomous agents.
  • Preprocess and analyze large-scale datasets to prepare them for model training and evaluation.
  • Collaborate with mentors and team members to debug, optimize, and deploy models.
  • Research the latest advancements in GenAI and ML to inform our technical strategy.
  • Document your work and present your findings to the team.
  • Candidate must be pursuing a Bachelor's Degree or Master's Degree in one of the following degree programs: Computer Science, Software Engineering, Computer Engineering, Information Technology or Information Systems.
  • Currently pursuing a Bachelor's or Master's degree with a graduation date on or after December 2026.
  • Strong proficiency in Python and should be comfortable with libraries like NumPy, Pandas, and Scikit-learn etc.
  • Demonstrated experience with machine learning techniques, including a solid understanding of concepts like classification, regression, and algorithms such as Random Forest, Gradient Boosting, or similar.
  • Understanding of fundamental GenAI concepts, including large language models (LLMs), transformers, and prompt engineering.
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