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Job Description:
Microchip Technology Inc. is seeking Senior Applications Engineer to support the development of Edge AI / Machine Learning demonstrations
on Microchip MCU, MPU, and FPGA platforms.
This role focuses on creating, validating, and documenting reference designs and demonstrations that enable customers to deploy AI/ML workloads on resource-constrained embedded systems. The successful candidate will work closely with internal engineering, marketing, and field teams to enable customers through high-quality demos, example code, and technical collateral.
Join our growing Edge AI team!
Key Responsibilities:
Develop Embedded applications using Microchip AI offerings demonstrating product capabilities and features set with focus on Edge AI based solutions.
Develop reference solutions and proof of concept demos to assist customers in designing, developing & troubleshooting Edge AI applications like Sensor analytics implementation using AI on MCU platforms using TinyML.
Attend meetings with various stakeholders to understand the key customer issues and come up with solutions to solve them
Participate in Development, review and implementation of AI/ML applications, models and algorithms optimized for edge computing environments in our cloud-based development and application space.
Use AI models in various platforms using TFLite, Tensorflow, ONNX, Pytorch based technologies.
Provide presentations and trainings on technical topics to customers and other stakeholders
Provide feedback on improvements in Microchip’s hardware, software, tools and documentation targeting Edge AI solutions.
Work closely with product management to help define project requirements, milestones, and deliverables.
Work with software engineers to develop methodologies in gathering, applying and evaluating data for consumption by AI models running on Edge AI hardware.
Train and tune AI models for efficient execution on hardware platforms.
Utilize best practices in software development, including code reviews, unit testing, integration and continuous integration.
Stay up-to-date with the latest advancements in AI/ML and edge computing technologies to ensure our solutions remain at the cutting edge.
Work in a team environment, developing and fostering a culture of innovation and continuous improvement.
Requirements/Qualifications:
Bachelor’s, Master’s degree in Computer Science, Electronics Engineering or related field.
10+ years of total experience in Embedded design and development and at least 2+ years of specific AI/ML based application development.
Proficient knowledge in using machine learning development languages, tools and frameworks, such as the MPLAB Machine Learning Development Suite and Python AI/ML libraries using TensorFlow/TFLite, Pytorch, Keras, and ONNX.
Prior experience on any part of sensor analytics in real systems, including circuit breakers, consumer appliances, power supplies, gas / water leakage etc. would be an advantage.
Prior experience implementing tiny ML class algorithm on ARM M0 to M7 class MCU and / or similar performance DSP would be preferred.
Solid programming experience in Embedded C and use of Embedded Software frameworks/ solutions and OS fundamentals.
Good knowledge of one of more communication protocols/interfaces such as I2C, SPI, UART as well as other peripherals such as ADC/DAC, PWM, RTC, WDT, Timer/Counters
Experience in Motor control/ USB/ Graphics will be an added advantage
Application layer software development experience on embedded systems. Ability to translate complex technical concepts into
simplified examples.
Work experience on IDE tools like MPLAB IDE/ IAR Workbench/ Keil MDK/ Atmel Studio or Linux environments
Exposure with RTOS/ Zephyr would be an added advantage
Team player with Strong written and verbal communication skills.
Must be highly motivated. Possess eager attitude toward learning new skills & technology.
Preferred Qualifications:
Experience in TinyML or Edge AI workflows.
Familiarity with use of computing platforms (AWS, Azure, GCP, OCI) and edge-to-cloud integration.
Knowledge of data collection, preprocessing, and training neural networks in data centers.
Solid understanding of edge computing architectures, including IoT devices, embedded systems, and real-time processing.
Experience with edge computing platforms and optimizing AI/ML models for resource-constrained devices.
Knowledge of signal processing and analysis in an ML framework.
Knowledge of security and privacy considerations in edge computing and cyber security development and analysis methods using ISO-21434 workflow requirements.
Travel Time:
0% - 25%
To all recruitment agencies: Microchip Technology Inc. does not accept unsolicited agency resumes. Please do not forward resumes to our recruiting team or other Microchip employees. Microchip is not responsible for any fees related to unsolicited resumes.
