AI-Enabled RAN Systems Developer

Ericsson; Stockholms kommun; On-site; SEK 894,000 - 1,175,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Stock Purchase Plan

Paid time off

Job summary

Ericsson Ottawa is seeking an AI in RAN System Developer to apply machine learning to optimize 5G/6G-ready RAN systems. You will shape AI-enabled features from prototyping to production, balancing performance with real-time constraints.

The role requires deep ML knowledge, strong software skills (C++, Python) and familiarity with telecom architectures, with a focus on productization and end-to-end delivery in a global telecom environment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Applied Mathematics, Telecommunications or a related discipline.
• Proven ML fundamentals and ability to select ML vs classical algorithms.
• Experience with resource-constrained systems and deployment feasibility on telecom platforms.

Responsibilities

• Drive AI/ML-enabled RAN function design and ensure real-time productization.
• Develop, evaluate and optimize AI-based solutions for scheduling, mobility, link adaptation, and RRM.
• Integrate AI solutions into existing RAN products and production workflows.
• Evaluate problems and decide when ML adds value over classical approaches.
• Design experiments, data collection strategies and validation methodologies for AI solutions.
• Analyze data and translate insights into deployable capabilities to improve network metrics.
• Optimize AI models for CPU, memory, power, and latency budgets.
• Contribute to AI lifecycle practices and best practices for RAN products.

Skills

ML fundamentals

Resource-constrained

C++

Python

RAN knowledge

Education

Bachelor's or Master's in CS/EE/Applied Math/Telecom

Tools

TensorFlow

PyTorch

CI/CD

Embedded systems

Job description

Ericsson Ottawa is seeking an AI in RAN System Developer to apply machine learning to optimize 5G/6G-ready RAN systems. You will shape AI-enabled features from prototyping to production, balancing performance with real-time constraints.

The role requires deep ML knowledge, strong software skills (C++, Python) and familiarity with telecom architectures, with a focus on productization and end-to-end delivery in a global telecom environment.