• Develop and optimize recommendation engines for products, services, and personalized customer experiences
• Design and implement NLP solutions for customer interactions, text analysis, and automation
• Create and deploy generative AI applications to enhance telecommunications services and operations
• Understand and analyze business problems deeply, working with stakeholders to define problem scope and success criteria
• Shape end-to-end solutions based on thorough problem analysis and business requirements
• Assess and evaluate emerging trends in GenAI and NLP, providing recommendations for adoption
• Stay current with cutting-edge developments in recommendation systems and their applications
• Apply AI to network optimization, customer value management, and operational efficiency
• Conduct exploratory data analysis to uncover patterns and insights
• Develop specialized models for telecom-specific data (call patterns, network performance, customer journey)
• Apply telco domain knowledge to develop industry-specific solutions (churn prediction, network optimization, fraud detection)

• Strong programming skills in Python and experience with AI/ML frameworks
• Strong object-oriented programming (OOP) principles with knowledge of design patterns for software development
• Flexibility to learn other programming languages and frameworks as needed
• Ability to work with APIs and contribute to frontend development when required
• Demonstrated experience building recommendation systems at scale
• Expertise in NLP techniques, frameworks, and applications
• Practical experience with generative AI models and their implementation
• Proficiency in statistical analysis and experimental design
• Experience with big data technologies and SQL
• Strong problem-solving and analytical thinking skills
• Understanding of data privacy considerations and ethical AI development

Preferred Qualifications

• Experience with LLMs and transformer-based architectures
• Knowledge of advanced prompt engineering and LLM optimization techniques
• Familiarity with collaborative filtering, content-based, and hybrid recommendation approaches
• Experience with embeddings and vector representations for recommendation and NLP tasks
• Experience with LangChain and LangGraph frameworks
• Background in telecommunications or related industry applications of AI
• Experience with cloud-based AI/ML services and distributed computing