2027 Internship - Systems Engineering - Power & Control

Job description

For over four decades, Cirrus Logic has been propelled by the top engineers in mixed-signal processing. Our rockstar team thrives on solving complex challenges with innovative end-user solutions for the world's top consumer brands. Cirrus Logic is also known for its award-winning culture, which was built on a foundation of inclusion and fairness, meaningful community engagement, and delivering enjoyable employee experiences at every turn. But we couldn’t do it without our extraordinary workforce – and that’s where you come in. Join our team and help us continue to make Cirrus Logic an exceptional place to grow your career! Are you a builder at the frontier of Edge AI/ML, eager to apply your academic research to high-impact, real-world problems? Do you thrive in ambiguous spaces where data, silicon, and algorithms intersect? Cirrus Venture Labs (CVL) may be the place for you. CVL is Cirrus Logic’s technology accelerator, chartered to develop disruptive, scalable, and monetizable innovations. Our vision is to be a globally recognized innovation engine that shapes semiconductor markets by embedding intelligence directly where signals originate—across Voice, Sense, and Control domains. As an ML Research & Systems Intern, you will work alongside our seasoned engineers to turn ambitious hypotheses into validated prototypes. This is not a "shadowing" role; you will be hands-on, contributing to our prototyping pipelines, data curation, and model optimization for deployment on constrained Edge and mixed-signal systems. Responsibilites System Modeling & Simulation: Develop system-level models using MATLAB, Simulink, Simscape, and related tools to analyze electrical, mechanical, and control system behavior. Evaluate system dynamics, stability, transient response, efficiency, and performance tradeoffs. Control Systems Development: Support the modeling and evaluation of linear and nonlinear control systems, including feedback control, state-space methods, motor control techniques, and advanced control algorithms. Explore opportunities for adaptive, predictive, and ML-augmented control. Power Electronics & Distribution: Analyze isolated and non-isolated power conversion topologies, power distribution architectures, and associated electrical and thermal considerations. Support the evaluation of converter performance, control strategies, and system-level integration. Hardware Design & Prototyping: Contribute to schematic capture, PCB design, component selection, and development of experimental hardware platforms. Participate in board bring-up, debugging, and rapid iteration of proof-of-concept systems. Lab Testing & Measurement: Perform hands-on testing and characterization using oscilloscopes, power analyzers, electronic loads, signal generators, and other laboratory instrumentation. Develop experimental setups and measurement methodologies to evaluate system performance. Simulation-to-Hardware Validation: Correlate analytical and simulation results with experimental measurements, investigate discrepancies, and refine system models and technical assumptions. Python & Data-Driven Engineering: Develop Python-based tools and scripts to automate simulations, process experimental data, visualize results, and support system characterization. Explore opportunities to incorporate machine learning into engineering analysis and experimentation. Technology Exploration: Research emerging technologies and engineering approaches in power electronics, motor control, advanced sensing, and intelligent physical systems. Help evaluate the feasibility and performance potential of new technical concepts. Cross-Functional Collaboration: Work closely with Innovation Managers, systems architects, and engineering teams to translate early-stage technical hypotheses into measurable experiments, engineering models, and proof-of-concept demonstrations. Ecosystem Partner Engagement: Participate in technical discussions and collaborative development activities with startups, technology vendors, universities, and research institutions. Support the evaluation and integration of emerging technologies from external partners. Customer Engagement: Collaborate with CVL team members in customer-facing technical discussions to understand application requirements, system constraints, and integration challenges. Help translate customer feedback into technical experiments and prototype requirements. Technical Communication: Document experimental findings, present technical results, and contribute to engineering reviews that inform architectural decisions and the progression of innovation initiatives. Required Skills and Qualifications Educational Background: Currently pursuing a Master's or Ph.D. degree in Electrical Engineering, Computer Engineering, Control Systems, Power Electronics, or a related technical discipline. Technical Foundation: Strong academic foundation in electrical circuits, power electronics, system dynamics, and feedback control theory. Modeling & Simulation: Experience using MATLAB, Simulink, or comparable tools for system modeling, simulation, and analysis through academic research, coursework, or engineering projects. Control Systems: Understanding of linear and nonlinear control systems, stability analysis, and fundamental control techniques. Power Electronics: Familiarity with DC/DC conversion, switching power supplies, motor drives, and isolated or non-isolated power architectures. Hardware & Prototyping: Exposure to circuit design, schematic capture, PCB development, or hardware prototyping through academic research, coursework, or personal projects. Laboratory Skills: Experience with electronic test equipment and a strong interest in hands-on experimentation, measurement, and hardware debugging. Analytical Thinking: Strong problem-solving skills and the ability to apply first-principles engineering analysis to unfamiliar technical challenges. Collaboration & Communication: Ability to work effectively in multidisciplinary teams, communicate technical findings clearly, and operate in an exploratory research and development environment. Preferred Skills and Qualifications Advanced Power & Control Systems: Graduate research or project experience in power electronics, motor drives, robotics, mechatronics, or cyber-physical systems. Motor Control Techniques: Familiarity with field-oriented control (FOC), sensorless control, model predictive control, or other advanced motor and actuator control techniques. Simulation Tools: Experience with LTspice, PLECS, PSIM, or similar circuit and power electronics simulation platforms. Hardware Development: Experience designing, assembling, bringing up, and debugging prototype PCBs or embedded hardware systems. Machine Learning & Python: Proficiency in Python for scientific computing, data analysis, and machine learning, including familiarity with libraries such as NumPy, SciPy, pandas, scikit-learn, PyTorch, or TensorFlow. ML Development Workflows: Familiarity with standard machine learning workflows, including data collection and preprocessing, feature engineering, model development, training, validation, benchmarking, and performance evaluation. ML for Physical Systems: Exposure to applying machine learning techniques to physical systems, including system identification, predictive modeling, anomaly detection, adaptive control, or optimization of power and electromechanical systems. Simulation & Data Integration: Experience using Python to automate simulations, process experimental data, and integrate analytical or physics-based models with data-driven approaches. AI-Assisted Engineering: Interest or experience leveraging modern AI development tools, coding assistants, and emerging agentic workflows to accelerate research, simulation, software development, and engineering experimentation. Embedded Systems & Programming: Experience with C/C++, embedded firmware development, microcontrollers, or real-time control implementation. External…