Role summary
We are building intelligent sensing systems by integrating diverse sensor technologies into unified platforms.
The Senior Sensor Systems & Integration Engineer will lead the end-to-end integration of multi-modal sensor systems from hardware interfaces and data acquisition to signal processing and system validation.
This is a hands-on role focused on building robust, real-world sensing systems that operate reliably outside the lab, working across hardware, embedded, and AI/ML components.
Key responsibilities
- Integrate diverse sensor modalities (optical/thermal, acoustic/audio, RF/radar (mmWave, FMCW), motion/IMU, cameras including RGB/depth/event-based, and environmental sensors)
- Design and implement sensor interfaces using SPI, IC, UART, CAN, and Ethernet
- Develop and manage data acquisition pipelines for reliable, low-latency sensor data
- Lead sensor selection, evaluation, and characterization based on performance, noise, and environmental constraints
- Prototype, deploy, and validate sensor systems in real-world conditions
- Implement sensor synchronization and calibration across multiple modalities
- Develop signal processing pipelines (filtering, denoising, feature extraction)
- Deployment of sensing systems on embedded platforms and edge AI device
- Debug system issues across hardware, firmware, and data pipelines
- Collaborate with AI/ML teams; support multimodal sensor fusion and deployment on edge systems
- Work with time-series and waveform data from different sensor modalities
Required skills and competencies
- Master's or PhD's degree in Electrical Engineering, Electronics, Mechatronics, or a related field
- 7+ years of experience in sensor systems, hardware integration, or embedded sensing platforms
- Strong experience with sensor interfaces (SPI, IC, UART, CAN, Ethernet)
- Hands-on experience integrating and deploying multi-sensor systems
- Solid understanding of signal processing for time-series/sensor data
- Experience working with data acquisition systems and sensor data pipelines
- Strong debugging skills across hardware, system, and data levels
Desirable
- Experience with multiple sensing modalities (RF/radar, acoustic, IMU, cameras, optical, etc.)
- Experience with sensor calibration and synchronization
- Familiarity with embedded Linux or edge platforms
- Exposure to ML workflows or sensor fusion systems
Key Attributes
- Strong systems thinker with hands-on mindset
- Comfortable working across hardware, embedded, and data layers
- Pragmatic, detail-oriented, and focused on real-world performance
- Curious about sensing technologies and complex signal environments
- Able to operate independently in a fast-paced startup environment
