Title : Gen AI IOT Developer
Overall experience: 510 yrs
Preferred Location: Noida
Mandatory Skills: GenAI with IoT experience
Skills:
Programming Skills:
Proficiency in languages like Python R or Java with a focus on AI libraries (TensorFlow PyTorch).
- C/C: Common for firmware and lowlevel programming.
- Python: Used for scripting data analysis and backend services.
- JavaScript: Often used in web interfaces and for Node.js applications
Machine Learning: Understanding of supervised unsupervised transfer and reinforcement learning techniques.
Data Preprocessing: Skills in cleaning transforming and preparing data for AI models.
Embedded AI: Knowledge of deploying AI models on edge devices with limited resources.
IoT Protocols: Familiarity with protocols like MQTT and CoAP for device communication.
Realtime Processing: Skills in handling realtime data streams and analytics.
Edge Computing Knowledge:
Understanding of edge architecture and how it differs from cloud computing.
- Familiarity with edge devices gateways and local data processing.
Model Optimization:
Skills in optimizing AI models for resourceconstrained environments (quantization pruning).
- Experience with frameworks like TensorFlow Lite or ONNX for deploying models on edge devices.
Embedded Systems:
Knowledge of embedded programming languages (C C) and platforms (Raspberry Pi NVIDIA Jetson).
- Understanding of hardwaresoftware integration.
- Understanding microcontrollers and hardware platforms (e.g. Arduino Raspberry Pi).
- Familiarity with RealTime Operating Systems (RTOS).
Networking Protocols:
Familiarity with protocols for edge communication (MQTT CoAP etc.).
- Knowledge of realtime data transmission and lowlatency networking.
- Knowledge of IoT protocols like MQTT CoAP HTTP/HTTPS.
- Understanding of networking concepts (TCP/IP DNS etc.).
Security Practices
Skills in securing edge devices and data at rest and in transit.
- Understanding of device authentication and identity management.
Monitoring and Maintenance:
Experience with monitoring tools to track performance and health of edge AI deployments.
Cloud Platforms and Services
- Familiarity with cloud IoT platforms (AWS IoT Google Cloud IoT Azure IoT).
- Experience with cloud computing concepts and services (storage databases analytics).
DevOps and Continuous Integration/Continuous Deployment (CI/CD)
- Experience with version control (Git) and CI/CD tools (Jenkins Travis CI).
- Familiarity with containerization (Docker Kubernetes).
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