About the role
Required Technical Skill Set 1. Programming: Python (strong), SQL 2. ML Frameworks: Scikit learn, TensorFlow / PyTorch 3. GenAI / LLMs: OpenAI / Azure OpenAI, LangChain, vector databases 4. Data Engineering: ETL pipelines, data modeling, data validation 5. Cloud: Azure / AWS / GCP (at least one)
Must Have 1.Python 3.ML 4.Gen AI frameworks 4.ETL and Data Engg
Roles and Responsibilities 1. Design, develop, and deploy machine learning models for prediction, classification, and optimization use cases 2. Apply supervised, unsupervised, and time series techniques 3. Evaluate models using appropriate metrics (accuracy, precision/recall, RMSE, Sharpe ratio, etc.) 4. Build and optimize LLM-based applications (chatbots, assistants, summarization, Q&A) 5. Implement Retrieval Augmented Generation (RAG) using vector databases 6. Work with prompt engineering, model evaluation, and LLM guardrails 7. Integrate LLMs with tools, APIs, and enterprise systems 8. Perform feature engineering and model tuning 9. Participate in code reviews and contribute to architecture decisions. 10. Experience with financial domain data (risk, portfolio, pricing, forecasting) 11. Knowledge of model evaluation frameworks and LLM as judge concepts 12. Exposure to Hugging Face, fine tuning, or open source LLMs 13. Experience with Spark / Databricks
Qualifications: BACHELOR OF ENGINEERING