I design and deploy high-performance computer vision systems for real-world industrial environments.

• ⚡ Real-time pipelines (30+ FPS) under constrained hardware
• 🧠 GPU acceleration (CUDA / TensorRT / zero-copy)
• 🏭 Industrial vision systems (inspection, automation, edge deployment)
• 🔧 Robust perception under non-ideal conditions (lighting, noise, reflections)

• 🚀 Optimized production pipelines from ~14 → 30 coins/sec
• ⚙️ Designed lock-free, zero-copy architectures for deterministic performance
• 🧠 Built multi-stage CV pipelines: segmentation → orientation → classification → defect detection
• 📡 Deployed systems on Jetson (edge AI) with real-time streaming and multi-client support

I specialize in systems where hardware meets AI, focusing on:

• Deterministic real-time processing
• GPU memory optimization (cudaHostRegister, zero-copy)
• Scalable vision architectures (multi-process, shared memory)
• Industrial communication (CAN / J1939 / Modbus)

Real-time inspection system built for high-throughput production lines.

• 🧩 C++ camera producer + Python consumers (shared memory)
• ⚡ Zero-copy GPU pipeline
• 🔄 Lock-free double buffering (0 ms overhead)
• 🧠 CV pipeline: segmentation → alignment → classification → defect detection
• 📡 WebSocket streaming to multiple clients

fromtypingimportDict, ListclassEngineer:
def__init__(self):
self.name="Gerald Cainicela"self.role="Embedded & CV Engineer"self.location="Lima, Peru 🇵🇪"self.focus= [
"Real-Time Computer Vision",
"Edge AI & Inference Optimization",
"Industrial Embedded Systems",
"Protocol Engineering (CAN/J1939)"
]
defget_stack(self) ->Dict[str, List[str]]:
return {
"vision": ["CUDA", "TensorRT", "YOLO"],
"embedded": ["ESP32", "FreeRTOS", "STM32"],
"edge": ["Jetson", "Docker", "OpenVINO"],
"plc": ["CODESYS", "IEC 61131-3", "Modbus"],
}
asyncdefdeploy(self, target: str) ->str:
returnf"Optimized & deployed to {target}"

#include<memory>
#include<vector>
#include<string>
#include<map>classEngineer {
const std::string name_{"Gerald Cainicela"};
const std::vector<std::string> focus_{
"Real-Time CV", "Edge AI",
"Industrial IoT", "Protocol Eng."
};
public:autogetStack() constnoexcept {
return std::map<std::string,
std::vector<std::string>>{
{"vision", {"C++20", "CUDA", "TensorRT"}},
{"embedded", {"ESP-IDF", "FreeRTOS", "ARM"}},
{"edge", {"Jetson", "Docker", "ONNX"}},
{"comms", {"CAN", "J1939", "Modbus"}}
};
}
template<typename T>
[[nodiscard]]autooptimize(T&& pipeline) {
return std::make_shared<std::decay_t<T>>(
std::forward<T>(pipeline));
}
};

Specialized in real-time computer vision and industrial embedded systems. I build high-performance pipelines for edge inference, industrial bus communication, and robust production deployments.

_{Lima, Peru · 2026}