Researcher Engineering

About This Role The Researcher will play a critical role in developing innovative, early‑stage (early TRL) technologies that support Kidde’s long‑term leadership in residential fire and life safety. This role focuses on strategic, emerging, and disruptive technologies, contributing foundational research that enables future product platforms. This is a hands‑on, highly technical role ideal for someone who thrives in exploratory research, rapid prototyping, and cross‑disciplinary experimentation Key Responsibilities Research & Technology Exploration Conduct research on emerging technologies in sensing, electronics, embedded systems, and AI/ML relevant to fire and life safety. Translate research ideas into practical, testable solutions Develop early‑stage prototypes and proof‑of‑concept systems to evaluate feasibility and performance. Explore innovative approaches in optical smoke detection, CO/IAQ sensing, particulate sensing, and multi‑modal detection. Analyze experimental data, sensor outputs, and environmental behavior, interpret results to guide technology maturation. Support progression of technologies through early TRLs by identifying risks, proposing mitigation strategies, and documenting findings. Collaboration & Technical Contribution Work closely with engineers, product teams, and subject‑matter experts to align research with future product needs. Contribute technical insights to technology roadmaps and long‑term innovation strategies. Participate in cross‑functional discussions to ensure research outcomes are actionable and relevant to downstream development teams. Documentation & Knowledge Development Document research results, experimental methods, prototype designs, and analytical findings. Support intellectual property (IP) development by identifying novel concepts and contributing to invention disclosures. Required Qualifications Education & Experience Master’s degree or Ph.D. in Engineering, Computer Science, Physics, or a related technical field. Strong research capabilities with experience in early‑stage technology development. Strong problem-solving skills and ability to work in ambiguous environments Technical Skills Advanced AI/ML Expertise Experience with ML frameworks such as TensorFlow, PyTorch, or scikit‑learn. Ability to design, train, and evaluate models for signal processing, anomaly detection, sensor fusion, and classification. Familiarity with embedded or edge‑AI deployment (TinyML, TensorFlow Lite, Edge Impulse). Embedded Firmware & Systems Engineering Proficiency in C/C++, embedded Linux, RTOS, and low‑power microcontroller platforms (ARM Cortex‑M, ESP32, Nordic, etc.). Experience with sensor drivers, communication stacks, and real‑time data acquisition. Ability to develop and execute automated tests and simulations in a hardware-in-the-loop (HIL) environment. Understanding of low‑power design, memory optimization, and hardware‑software integration. Electronics & Sensing Technologies Hands‑on experience with sensor integration. Knowledge of optical detection principles, gas sensing (CO, IAQ), particulate sensing, and environmental monitoring technologies. Ability to evaluate sensor performance, noise characteristics, calibration methods, and environmental compensation techniques. Data Analytics & Signal Processing Strong skills in Python, MATLAB, or similar tools for data analysis, modeling, and visualization. Experience with filtering, feature extraction, time‑series analysis, and statistical modeling. Ability to design experiments, analyze large datasets, and derive actionable insights. Wireless Communication & IoT Familiarity with BLE, Wi‑Fi, Zigbee, Thread, Matter, or other low‑power wireless protocols. Understanding of IoT architectures, cloud connectivity, and device‑to‑device communication. Prototyping & Lab Skills Experience with rapid prototyping tools (3D printing, breadboarding, test jigs and CAD software). Proficiency with lab equipment such as oscilloscopes, logic analyzers, signal generators, and environmental test chambers. Ability to design and execute experiments to validate early‑stage concepts Preferred Qualifications Experience with fire safety, environmental sensing, or life‑safety technologies. Familiarity with simulation tools, data modeling, or machine learning frameworks. Experience with IoT ecosystems, wireless communication protocols, and smart home integrations. Ability to translate research findings into actionable engineering recommendations Data analytics and inferencing with particulate matter and aerosols Material Science background