Edge AI Engineer - Data Modeling

About BeGig :

BeGig is the leading tech freelancing marketplace.

We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent.

By joining BeGig, youre not just taking on one role - youre signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise.

Your Opportunity :

Join our network as an Edge AI Developer and bring AI capabilities directly to edge devices- where speed, privacy, and offline access matter most.

Youll develop, deploy, and optimize machine learning models to run on low-power, low-latency hardware in real-world environments like IoT, robotics, automotive, and smart devices.

This fully remote role is available on an hourly or project-based basis.

Role Overview :

As an Edge AI Developer, you will :

- Build AI for the Edge : Develop and deploy optimized AI models that run directly on embedded or edge devices.

- Model Optimization : Use techniques like quantization, pruning, and compression to reduce model size and inference latency.

- Hardware Integration : Work with edge hardware platforms such as NVIDIA Jetson, Raspberry Pi, Coral TPU, and ARM-based boards.

- Deploy Offline Models : Package and deploy models for inference without requiring constant cloud connectivity.

- Performance Tuning : Ensure models are fast, accurate, and resource-efficient under real-time constraints.

- Toolchain Usage : Use platforms like TensorFlow Lite, ONNX, OpenVINO, or PyTorch Mobile for deployment and optimization.

Technical Requirements & Skills :

Experience : Minimum 2+ years in machine learning, embedded systems, or AI application development.

- Programming : Proficiency in Python and C/C++ for model integration, device communication, and real-time processing.

- Hardware Platforms : Familiarity with deploying AI models on Jetson Nano, Raspberry Pi, Intel

Neural Compute Stick, etc.

- Deployment & Testing : Ability to build testing frameworks to simulate edge scenarios and

monitor performance.

- Real-Time Considerations : Understanding of latency, thermal constraints, power

management, and memory limitations.

What Were Looking For :

- A developer passionate about running AI outside the cloud - on devices where speed, efficiency, and privacy are critical.

- A freelancer who can navigate hardware constraints and deliver smart, optimized ML models in production.

- Immediate Impact : Help startups deploy AI models into real-world environments - from warehouses to smart homes.

- Remote & Flexible : Work from anywhere and structure your engagement on your own terms - hourly or project-based.

- Future Opportunities : Be continuously matched with projects in IoT, robotics, and real-time edge AI.

- Growth & Recognition : Be part of a trusted network that values cutting-edge technical expertise and applied AI delivery