5G AI/ML Engineer & Application Modernization - Onsite
Simple Solutions
Job Description
Job Description
Job Title: Engineer – 5G AI/ML & Application Modernization
Location: Onsite daily in Bedminster, NJ
Duration: 6 Months with opportunity to go longer
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
Vacancy posted 3 days ago
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