About the role
CTO - AI & Hardware
360 Technology
Bengaluru | Hybrid | Experience: open, roughly 1-2 to 6-7 years | CTC: INR 15-60 LPA
360 Technology is establishing an AI lab. We are looking for an ambitious, hands-on technology leader who enjoys making AI work with physical devices. You will turn early ideas into working hardware-and-AI prototypes and own the system architecture from model to device.
What you will do
- Design and build experiments that combine AI with devices, sensors or embedded systems. Move quickly from an idea to a testable physical prototype.
- Own the full pipeline: device inputs, data collection, model selection, training or fine-tuning, inference and the resulting software or device response.
- Integrate firmware, sensors and connectivity over I2C, SPI, UART, CAN, MQTT and BLE. Work with hardware specialists when board-level design or fabrication is needed.
- Choose where inference runs: on-device, at the edge or in the cloud. Optimise with quantization, ONNX, TensorRT or TFLite, and measure accuracy, latency, memory, power and cost.
- Debug across hardware and software. Test real-world conditions, connectivity failures and safe fallback behaviour.
- Build repeatable deployment, device monitoring and OTA update processes. Protect device access and data, and document the build so others can reproduce it.
- Set the technical direction, guide other builders and explain practical trade-offs to non-technical stakeholders.
What we are looking for
- Evidence of a working AI-plus-hardware project that you built, tested and debugged yourself. Strong system architecture and problem-solving skills.
- Strong C/C++ and Python; embedded Linux and/or an RTOS such as FreeRTOS or Zephyr; comfort with Raspberry Pi, ESP32, STM32 or NVIDIA Jetson platforms.
- Experience deploying models outside a notebook with PyTorch, ONNX, TensorRT or TFLite, including quantization and the limits of real devices. OpenCV or audio pipelines are a plus.
- Hands-on sensor, peripheral and bus integration. Ability to read datasheets, use oscilloscopes or logic analysers, and diagnose failures at hardware-software boundaries.
- Curiosity, ownership and the patience to tinker. Comfortable with imperfect prototypes, fast experiments and learning unfamiliar tools.
- Computer vision, audio AI, robotics, IoT or camera systems. These are examples, not a requirement to know every platform.
- A short demo, repository or build log showing a physical prototype. Be ready to explain the hardware, model, your contribution, what failed and what you measured.
This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.