Description

Key Responsibilities

• Develop, deploy, and maintain machine learning models in production environments
• Work on NLP use cases such as text classification, sentiment analysis, and conversational AI
• Design and implement solutions using Large Language Models (LLMs) (e.g., BERT, GPT, RoBERTa)
• Apply fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG) techniques
• Perform data preprocessing, feature engineering, and model evaluation
• Work with large-scale structured and unstructured datasets
• Collaborate with cross-functional teams to translate business problems into ML solutions
• Present insights and results to both technical and non-technical stakeholders
• Continuously improve model performance, scalability, and efficiency

Required Qualifications

• 5+ years of experience in Data Science, Machine Learning, or AI-focused roles
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn)
• Hands-on experience with TensorFlow or PyTorch
• Proven experience with NLP and ML model development
• Strong understanding of AI/ML principles and LLMs
• Experience working with LLMs (BERT, GPT, RoBERTa)
• Hands-on experience with fine-tuning, prompt engineering, and RAG
• Experience with cloud platforms (AWS, Azure, or GCP)
• Strong SQL skills and experience handling large datasets
• Excellent communication and stakeholder management skills

Preferred Skills

• Experience with MLOps (deployment, monitoring, lifecycle management)
• Familiarity with CI/CD, Docker, Kubernetes
• Experience with model explainability (XAI)
• Knowledge of data governance, privacy, and compliance
• Experience with AI automation tools/frameworks
• Exposure to telecom or customer interaction data (nice to have)
• Experience working in Agile environments

Key Skills

Education

Bachelor's or Master's degrees