Build intelligence that works in the real world.
AI is moving beyond the cloud and into the physical world, where intelligence must interact with real signals, sensors, hardware, and physical constraints. At CloudIoT, we are interested in people who can bridge first-principles physics, electronics, embedded and edge computing, sensing and instrumentation, hardware-software co-design, and modern AI.
Electronics, RF & AI Systems Engineer / Researcher
We are looking for engineers, scientists, and technically curious problem-solvers with a strong foundation in electronics or physics and substantial hands-on laboratory experience. The ideal candidate is comfortable moving between theory, measurement, experimentation, troubleshooting, and system-level thinking.
- ✓Strong background in electronics, electrical engineering, applied physics, or a closely related field.
- ✓Hands-on experience building, testing, troubleshooting, and characterizing electronic and RF systems.
- ✓Understanding of signals, noise, bandwidth, measurement uncertainty, thermal limits, and system-level tradeoffs.
- ✓Interest in embedded and edge computing, sensing and instrumentation, hardware-software co-design, IoT, and AI-enabled physical systems.
- ✓Ability to work experimentally, document results clearly, analyze measured data, and turn observations into engineering decisions.
Experience with a broad range of laboratory, RF, microwave, networking, and data-acquisition equipment is especially valuable, including:
- ✓Oscilloscopes, including high-frequency and high-bandwidth oscilloscopes
- ✓Multimeters, voltmeters (VM), laboratory power supplies, and signal generators
- ✓Data acquisition (DAQ) systems
- ✓Signal analyzers and spectrum analyzers
- ✓Vector network analyzers (VNAs)
- ✓RF and microwave power meters
- ✓Antenna test systems and over-the-air (OTA) chambers
- ✓High-speed network encryptors and related network test environments
Closer to the hardware. Closer to the physics.
As edge-native models, neuromorphic architectures, scientific foundation models, and physics-informed AI continue to develop, practical innovation increasingly depends on people who understand the physical systems behind the data. The next generation of AI must do more than predict: it must perceive, reason, and act reliably in real environments.
That intersection of physics, electronics, sensing, communications, computing, and AI is where models become grounded and intelligent systems become deployable.
Interested in building what comes next?
If your background combines strong fundamentals with hands-on experimentation and you are excited by the convergence of electronics, RF systems, sensing, edge computing, and artificial intelligence, we would like to hear from you.
Send your résumé along with a brief introduction describing your technical background, laboratory experience, and areas of interest.