We are seeking a Full Stack 5G Software Engineer with expertise in 5G technologies to drive the development and enhancement of our Network as a Service platforms in 5G. You will work closely with cross-functional teams to build 5G native features that empower low-latency intelligent devices, improve user experiences, and optimize operations.
Key Responsibilities:
- Full Stack Development: Design, build, and maintain both the frontend and backend of our platforms using modern web technologies (React, Node.js, etc.), ensuring the integration of AI-powered features.
- 5G UPF/SMF Development: Design and implement 5G UPF/SMF and automation platform solutions to ensure network resources are allocated dynamically and efficiently.
- 5G Slicing Development: Design and implement 5G slicing solutions for dynamic and efficient network resource allocation.
- Collaboration & Cross-Functional Support: Collaborate with other engineering teams to integrate the 5G core with RAN, backhaul, and transport networks.
- AI & Machine Learning Models: Develop, train, and integrate machine learning and deep learning models, leveraging frameworks such as TensorFlow, PyTorch, or other relevant tools.
- Collaborative Development: Work closely with product managers, UX/UI designers, and other engineering teams to align on product requirements and deliver robust solutions.
- Scalability & Performance: Optimize platform architecture to handle large-scale, high-traffic applications with a focus on performance, security, and reliability.
Required Skills and Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field.
- Proven Experience: 7+ years as a Full Stack Developer in 5G and related domains, with 1-2 years working on AI-driven projects.
- Full Stack Expertise: Strong proficiency in both front-end (React, Angular, Vue.js) and back-end (Node.js, Express, Python, Java, etc.) development.
- AI and ML Expertise: Experience developing and deploying machine learning models, particularly agent-based AI models (reinforcement learning, multi-agent systems, autonomous decision-making).
- Database Knowledge: Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Redis).
- Cloud & DevOps: Experience with cloud platforms (AWS, Google Cloud) and containerization tools (Docker, Kubernetes).