6+ years of overall NLP/GenAI/Recommender Systems experience with considerable time spent in building enterprise grade solutions.
Proficiency in working with large datasets and performing data preprocessing on cloud platforms.
Practical experience in developing generative AI applications, including prompt engineering, Retrieval-Augmented Generation (RAG) applications.
Good understanding of LLM concepts and fundamental. Hands-on experience in leveraging LLMs for POCs and applied problem solving and integrating it into overall solution workflow.
Practical experience in developing various types of recommender systems, including content-based, collaborative filtering, or hybrid methods.
Strong programming skills in Python; experience with PySpark is a plus. Azure Cloud experience is mandatory.
Strong communication skills with the ability to clearly articulate data science outcomes.
Experience with version control systems like Git.
Familiarity with CI/CD practices, developing/consuming RESTful API is a plus.
Preferred Qualifications:
Familiarity with popular recommender system-related algorithms like ALS, KNN and LightFM.
Familiarity with transformer architecture, types of LLMs (encoder-only, encoder-decoder and decoder-only).
Some hand-on experience in solving NLP problem with/without GenAI will be a plus.
