5G AI/ML Engineer & Application Modernization - Onsite

Contract | Simple Solutions | United States Posted On 06/22/2026 Job Information Job Opening ID ZR_2943_JOB Work Experience 8-10 Years City Bedminster State/Province New Jersey 07921 Job Description 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 #J-18808-Ljbffr Simple Solutions