AGM-Data Engineer

Role Overview:

We are seeking a highly skilled and motivated Senior Data Scientist with deep expertise in Generative AI, Machine Learning, Deep Learning, and advanced Data Analytics. The ideal candidate will have hands-on experience in building, deploying, and maintaining end-to-end ML solutions at scale, preferably within the Telecom domain.

You will be part of our AI & Data Science team, working on high-impact projects ranging from customer analytics, network intelligence, churn prediction, to generative AI applications in telco automation and customer experience.

Key Responsibilities:

• Design, develop, and deploy advanced machine learning and deep learning models for Telco use cases such as:

  • Network optimization

  • Customer churn prediction

  • Usage pattern modeling

  • Fraud detection

  • GenAI applications (e.g., personalized recommendations, customer service automation)

• Lead the design and implementation of Generative AI solutions (LLMs, transformers, text-to-text/image models) using tools like OpenAI, Hugging Face, LangChain, etc.

• Collaborate with cross-functional teams including network, marketing, IT, and business to define AI-driven solutions.

• Perform exploratory data analysis, feature engineering, model selection, and evaluation using real-world telecom datasets (structured and unstructured).

• Drive end-to-end ML solution deployment into production (CI/CD pipelines, model monitoring, scalability).

• Optimize model performance and latency in production, especially for real-time and edge applications.

• Evaluate and integrate new tools, platforms, and AI frameworks to advance Vi’s data science capabilities.

• Provide technical mentorship to junior data scientists and data engineers.

Required Qualifications & Skills:

• 8+ years of industry experience in Machine Learning, Deep Learning, and Advanced Analytics.

• Strong hands-on experience with GenAI models and frameworks (e.g., GPT, BERT, Llama, LangChain, RAG pipelines).

• Proficiency in Python, and libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, etc.

• Experience in end-to-end model lifecycle management, from data preprocessing to production deployment (MLOps).

• Familiarity with cloud platforms like AWS, GCP, or Azure; and ML deployment tools (Docker, Kubernetes, MLflow, FastAPI, etc.).

• Strong understanding of SQL, big data tools (Spark, Hive), and data pipelines.

• Excellent problem-solving skills with a strong analytical mindset and business acumen.

• Prior experience working on Telecom datasets or use cases is a strong plus.

Preferred Skills:

• Experience with vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines.

• Exposure to real-time ML inference and streaming data platforms (Kafka, Flink).

• Knowledge of network analytics, geo-spatial modeling, or customer behavior modeling in a Telco environment.

• Experience mentoring teams or leading small AI/ML projects.