Engineer 5G AI/ML & Application Modernization

Position Overview:

senior-level 5G network engineering, AI/ML, and application modernization. This role will focus on transforming legacy applications, driving automation, and unlocking efficiencies across the company's 5G network infrastructure to support next-generation services and scale.

Key Responsibilities

• modernization and re-architecture of legacy telecom applications into scalable, cloud-native, Java-based platforms
• Apply AI/ML models to optimize 5G network performance, capacity planning, and fault management
• Identify and drive efficiency gains across the 5G ecosystem (RAN, Core, Transport, Edge)
• Partner with network engineering and IT teams to implement intelligent automation and AIOps solutions
• Develop high-performance Java applications supporting real-time telecom workloads
• Analyze large-scale network data to deliver actionable insights, cost optimization, and latency reduction
• Support innovation initiatives, POCs, and pilots tied to 5G monetization and operational excellence

Required Qualifications

Please focus on 2025/2026 PhD Graduates

• Masters Computer Science, Electrical Engineering, Telecommunications, or related discipline
• SMI, ORAN, 3GPP, Cloud, CI/CD, Python, Java,
• Experience in 5G architectures (RAN, Core, Edge, Open RAN exposure a plus)
• Development background in Java and modern application frameworks
• Hands-on experience with AI/ML technologies (TensorFlow, PyTorch, or equivalent)
• Proven experience in application transformation and performance optimization
• Experience working with SMI, ORAN, 3GPP, Cloud, CI/CD, Python, Java
• Background in telecom service provider environments

Preferred Qualifications

• Experience with network automation, orchestration, and observability platforms
• Familiarity with Kubernetes, microservices, and hybrid cloud architectures
• Exposure to AIOps, network analytics, and predictive maintenance models

Success Metrics

• Measurable reductions in network latency and operational costs
• Improved application performance, resiliency, and scalability
• Increased automation across network operations and service delivery
• Delivery of AI-driven insights that improve network efficiency and customer experience