AI-RAN System Development & Optimization:

Contribute to the design, development, and optimization of AI-RAN systems to improve the performance of wireless access networks.

Identify bottlenecks in RAN systems using AI technologies and implement solutions to enhance efficiency.

AI Models & Algorithm Application:

Apply machine learning, deep learning (including CNN, RNN, LSTM, etc.) to optimize network performance.

Participate in data preprocessing, feature engineering, model training, and validation to ensure model accuracy and efficiency.

Cross-Functional Collaboration:

Work closely with wireless communication engineers and R&D teams to ensure the successful deployment and delivery of AI-RAN systems.

Ensure the scalability and long-term optimization of AI-RAN systems through collaboration.

Continuous Learning & Innovation:

Stay up-to-date with the latest developments in AI technology and continuously enhance technical expertise.

Apply cutting-edge AI advancements to RAN systems, driving innovation and technology upgrades.

Educational Background:

Bachelor's degree or higher in Computer Science, Artificial Intelligence, Telecommunications Engineering, or a related field.

Experience:

Solid understanding of AI principles, machine learning, and deep learning technologies.

Prior experience in AI-RAN systems is a plus, though highly motivated recent graduates with strong learning capabilities are also encouraged to apply.

Technical Skills:

Proficiency in programming languages such as Python and C++ for developing and maintaining AI platform features.

Experience with machine learning and deep learning algorithms, and familiarity with frameworks like TensorFlow, PyTorch.

Practical experience with data analysis, training, and tools like Docker, Kubernetes, Git, etc.

Knowledge of at least one architecture and experience in high-performance computing (e.g., GPU, X86, ARM).

Soft Skills:

Strong desire for continuous learning and self-improvement.

Excellent communication skills and the ability to work well within a team.

Problem-solving ability and the capacity to make quick decisions in high-pressure situations.

Preferred Skills:

Knowledge of advanced AI fields such as multimodal AI, AIGC, NLP, and LLM.

Familiarity with RAG and Agent modes, and experience with tools like Langchain, LlamaIndex, and SemanticKernel is a plus.

Network Building Capability (Pytorch, TensorFlow, TensorRT)

For example, building CNN, YOLO, ResNet, LSTM, machine learning, etc.

Practical AI Implementation Experience

For example, RAG using LangChain.

Communication/RAN-related Background

For example, knowledge in 5G, Bluetooth, WiFi, etc

HR Manager: Effy Zhang
Email: effy.zhang@synaxg.com
Tel: 601137637706