Perform literature review on related works and evaluate a selected list of methodologies.
Select and optimize ML models suitable for anomaly detection using embedded frameworks (e.g., TensorFlow Lite for Microcontrollers)
Benchmarking inference latency and memory usage of selected ML models. Analyze the AI/ML hardware capabilities of the EFR32MG24 chip.
Profiling energy consumption during inference with and without the hardware accelerator.
Developing a real-world anomaly detection use case.
Propose an approach to integrate the solution in existing embedded data processing workflows
Your qualifications
Enrolled in engineering degree in Embedded Systems, Software Engineering, Computer Science or related subject for the duration of the internship
Passion in software development
All-rounded mentality and readiness to learn new skills and programming languages
Repository management experience using GIT
Good in C programming and at least one of the programming languages: C++/Java/C#/Python
Optional: prior experience in AI/ML related projects
Available for 6-12 months, 32-40 hours per week, preferred start date: October 1st
What you'll get in return...
Continuous mentoring and feedback throughout your internship.
Internship allowance; the exact amount depends on your situation (also towards rented accommodation or public transportation).
Paid leave on the basis of 1 day per month.
Extensive set of tools to drive your career, such as a personalized learning platform.
Opportunity to purchase products in the staff shop at reduced prices.
As an intern, you will be part of the intern program in the Netherlands, consisting of several events, trainings and networking opportunities with your peer students
Additional Information
About Signify
Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting. Through our leadership in connected lighting and the Internet of Things, we're breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond.
At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals. Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career.
Join us, and together, we'll transform our industry, making a lasting difference for brighter lives and a better world.
More about the role
Signify is one of the few companies in the world to achieve carbon neutrality and our next sustainability goals are even bolder: doubling our positive impact on the environment and society by 2025.
As embedded software intern, you get the opportunity to contribute to innovative projects focused on exploring how the latest advancements in Artificial Intelligence (AI), Machine Learning (ML), and Edge computing can be adopted to wireless embedded devices. These projects investigate how intelligent data processing and decision-making can be brought closer to the source of data. This includes optimizing models for resource constrained embedded devices, improving wireless bandwidth usage and enhancing sensory detection algorithms. You will gain hands-on experience with cutting-edge technologies and contribute to shaping the future of smart, connected IoT lighting systems.
We're on the lookout for forward-thinking innovators with a passion for sustainability. If you match this description, get in touch!
Topic description
Performance Evaluation and Application of Edge AI on Silicon Labs EFR32MG24 for Real-Time Anomaly Detection
This project investigates the viability of deploying lightweight machine learning models on the EFR32MG24 (or a similar) microcontroller, focusing on its integrated AI/ML accelerator. The goal is to evaluate the chip's computational performance, power efficiency, and real-time inference capabilities for practical edge applications such as anomaly detection in sensor data.
During this internship, the student will explore Silicon Labs Gecko SDK and AI/ML development packages to develop applications on embedded wireless sensor devices that are part of a smart IoT lighting system. The student will learn about the various techniques and tools used in the field and will gain hands-on experience working with real-world applications. The internship will provide an opportunity for the student to develop skills in embedded software development, AI/ML models, edge computing, as well as gain experience working on a complex and challenging project.