What are the responsibilities and job description for the AI/Machine Learning Engineering Intern position at Qorvo?
AI / Machine Learning Engineering Intern Experience Level : InternshipJob Type : InternLocation : TX - Richardson, USRequisition ID : 8247Qorvo’s Internship Program is designed for college students currently enrolled in an accredited Bachelor’s, Master’s, or PhD program. Qorvo offers real work experience, exposure to upper management, and the opportunity to pursue full-time opportunities, as available.Qorvo’s Internship Program offers : Challenging, skill-building assignmentsMentoring and coaching from industry expertsLunch & Learns and other learning opportunitiesCollaborative team-based work environmentNetworking and social eventsFinal presentation to business leadersQorvo’s AI / Machine Learning Engineering Internships are offered in our High Performance Analog business group. Specific projects and responsibilities will be determined based on the business needs at the time of the internship assignment.Responsibilities may include : Data Collection and Preprocessing : Gather and preprocess RF circuit data, including simulations, measurements, and real-world performance data.Feature Engineering : Identify relevant features and parameters for RF circuit analysis and design machine learning models to extract these features from raw data.Model Development : Create and train AI / ML models for RF circuit analysis, including predictive modeling, anomaly detection, and optimization algorithms.Algorithm Implementation : Implement AI / ML algorithms and integrate them into existing RF circuit analysis tools and workflows.Performance Evaluation : Evaluate the performance of AI / ML models and algorithms through extensive testing, validation, and benchmarking against traditional methods.Collaboration : Collaborate with RF engineers, software developers, and other cross-functional teams to ensure seamless integration of AI / ML solutions into RF circuit design and analysis processes.Documentation : Document your work, including algorithms, methodologies, and results, to facilitate knowledge sharing and future improvements.Qualifications : Currently enrolled in a graduate-level program in AI / MLStrong background in AI / ML, including experience with TinyML and embedded applicationsKnowledge of RF circuits and familiarity with simulation tools (e.g., Cadence, ADS, HFSS) is a plus.Strong problem-solving skills and the ability to work independently and collaboratively in a team.Excellent communication skills and the ability to present findings and results effectively.#J-18808-Ljbffr
