AI Technology Student Assignment: Production Deployment of Neural Network Architecture at Signify

<h3>Job Title</h3>AI Technology Student Assignment: Production Deployment of Neural Network Architecture at Signify<p></p><h3>Job Description</h3><h2><b>About Signify</b></h2><p>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.</p><p></p><p>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.</p><p></p><p>Join us, and together, we’ll transform our industry, making a lasting difference for brighter lives and a better world. You light the way.</p><p></p><p><b>More about the role</b></p><p>This is an exciting job opportunity for you to light the way as an AI Technology Researcher in Eindhoven with Signify. You will continue to develop the following research assignment:</p><p></p><p><b>Assignment Scope</b></p><p><b>Phase 1: Model Familiarization</b></p><ul><li><p>Review and understand the existing AI architecture and neural network model.</p></li><li><p>Bring the current model online and validate its functionality.</p></li></ul><p><b>Phase 2: Model Generalization</b></p><ul><li><p>Expand the model to improve robustness under varying office conditions.</p></li><li><p>Define configurations for collecting additional training data.</p></li><li><p>Collect and preprocess new datasets.</p></li><li><p>Retrain the model for generalization.</p></li><li><p>Validate performance on unseen setups and report quality metrics, referenced against existing rule-based sensing.</p></li></ul><p><b>Phase 3: Production Deployment Options</b></p><ul><li><p>Propose concrete electronic design and deployment strategies for hosting the model in a production environment.</p></li><li><p>Evaluate options such as:</p><ul><li><p><b>Cloud-based inferencing</b></p></li><li><p><b>Edge device inferencing</b></p></li><li><p><b>Dedicated AI chipsets</b></p></li></ul></li><li><p>Consider trade-offs in latency, cost, scalability, and maintainability.</p></li></ul><p></p><h2><b>More about you</b></h2><ul><li><p>Strong background in <b>AI/ML engineering</b>.</p></li><li><p>Hands-on experience with:</p><ul><li><p><b>Neural network training and optimization</b></p></li><li><p><b>TensorFlow or similar frameworks</b></p></li><li><p><b>Deployment of AI models on real-world devices or production environments</b></p></li></ul></li><li><p>Ability to work with sensor data and design practical solutions for embedded or cloud systems.</p></li></ul><p></p><h2><b>Everything we’ll do for you</b></h2><p>You can grow a lasting career here. We’ll encourage you, support you, and challenge you. We’ll help you learn and progress in a way that’s right for you, with coaching and mentoring along the way. We’ll listen to you too, because we see and value every one of our 30,000+ people.</p><p></p><p>We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas. With a global workforce representing 99 nationalities, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together.</p><p></p><p>Come join us, and together we can light the way.</p>