Build datasets, experiment pipelines, and automated analysis tools to evaluate system behavior and algorithm performance.
Create reproducible tests and experiments across software builds and algorithm versions using defined scenarios, configurations, and KPIs.
Support simulation verification and validation activities, including comparison with lab results and analysis of model behavior.
Build automated unit, component, end-to-end, regression, and performance tests and integrate them into CI/CD workflows.
Improve simulation speed, usability, observability, and automation so engineering teams can run repeatable experiments independently.
Debug issues across C/C++, Python, MATLAB, system software, configuration, and reference measurements.
Document assumptions, supported scenarios, limitations, and experiment results in a clear and structured way.
- Work closely with RAN, PHY, system, AI/ML, automation, and validation teams to turn engineering questions into measurable experiments.
- What you bring:
- B.Sc. in Electrical Engineering or an M.Sc. in a relevant field.
At least 2 years of hands-on software development experience in communication systems or a related telecom environment.
Strong software development skills in C or C++ and Python.
Good understanding of communication systems and the ability to learn new technologies and system concepts quickly.
Experience working in Linux development environments with Git, automated testing, and modern software development practices.
Strong analytical and problem-solving skills, with the ability to investigate complex technical issues independently.
Good communication skills and the ability to work effectively with software, system, algorithms, and validation teams.
- Simulation experience is not required; candidates with strong software and communication-system backgrounds are encouraged to apply.
- Nice to have:
- Experience with simulation environments, system-level modelling, or hardware-in-the-loop testing.
Knowledge of LTE and/or 5G NR, RAN, modem/PHY, or wireless communication systems.
Experience with MATLAB and communication-system simulation or analysis tools.
Hands-on experience with scientific computing and data analysis using NumPy, SciPy, pandas, or similar tools.
Exposure to AI/ML, time-series analysis, signal processing, or network optimization.
Familiarity with PyTorch, TensorFlow, Hugging Face, or other machine-learning frameworks.
Knowledge of digital communications and signal processing concepts.
Experience with automated testing, containers, CI/CD, or cloud development environments.
Familiarity with SDR, radio test equipment, lab automation, or field-log analysis.
