Design, develop and deploy advanced AI/ML models for telecom use cases such as: Network optimization, Traffic prediction and anomaly detection, QoS/QoE modeling and root cause analysis
Apply and adapt state-of-the-art AI techniques, including: Deep Learning (CNNs, RNNs, Transformers), Reinforcement Learning for network optimization, Time-series modeling at scale
Work deeply with real telecom network data (3G/4G/5G), understanding KPIs, counters, and traffic dynamics
Build production-ready solutions, ensuring scalability, performance, and reliability
Collaborate closely with data engineers and telecom experts to integrate AI models into real systems
Act as a technical reference within the team, contributing to best practices and code quality
Explore and apply Generative AI and LLM-based approaches to telecom use cases
Requirements
Bachelor’s or Master’s degree in Telecommunications Engineering (or related field)
6–8+ years of hands-on experience applying Machine Learning in technical environments
Strong, practical expertise in telecom networks (RAN, KPIs, traffic behavior)
Proven experience working with telecom network dataset
Deep knowledge of: Machine Learning & Deep Learning Neural Networks and model optimization
Time-series analysis
Strong programming skills in Python (NumPy, Pandas, PyTorch/TensorFlow)
Experience with SQL/NoSQL databases
Exposure to Generative AI / LLM technologies (prompt engineering, RAG pipelines, fine-tuning) and interest in applying them to telecom operations or network management contexts
Strong analytical mindset and problem-solving capabilities
English level B2+
Tech Stack
NoSQL
Numpy
Pandas
Python
PyTorch
SQL
Tensorflow
Benefits
Health insurance
Flexible Compensation Plan as an enterprise benefit
Annual training budget to help you stay technologically up to date and grow professionally
Time flexibility: our life is not just a working day; we give you flexibility both in entry and exit.
Reduced working day on Fridays and Summer (July and August).