EY GMS - GST-Data Scientist AI Engineer-Senior 

India, Karnataka, Bengaluru 

189671980

Key Responsibilities

• Develop reusable AI/ML models and end-to-end data science assets / products.
• Build and deploy LLM-based applications, including fine-tuning, prompt engineering, and RAGs.
• Translate domain challenges into data science problems with actionable solutions.
• Perform exploratory data analysis (EDA) to design optimal approaches.
• Rapidly prototype and iterate using ML/DL and LLMs.
• Deploy and manage models in Azure cloud environments.
• Mentor junior team members to foster growth and ensure quality deliverables.

LLM Tools & Frameworks

• Pretrained LLMs: OpenAI (GPT series), Gemini, LLaMMa, DALL-E, Hugging Face Transformers, T5, BERT, RoBERTa, etc.
• Fine-tuning Frameworks: Hugging Face Trainer, LoRA, PEFT etc.,
• Prompt Engineering Tools: LangChain, LangGraph, Semantic Kernel, Guidance etc.,
• Vector Databases: Pinecone, Weaviate, FAISS, Chroma etc.,
• LLM Evaluation Tools: OpenAI Evaluation Toolkit, Language Model Evaluation Harness etc.,
• Retrieval Mechanisms: BM25, Dense Passage Retrieval (DPR), Hybrid Search etc.,

Machine Learning & Deep Learning

• Algorithms: XGBoost, LSTM, CNN, Transformers, Random Forests etc.,
• Techniques: Transfer learning, Hyperparameter tuning, model training, and deployment.

Programming, Databases, and Frameworks

• Languages: Python
• ML/DL Frameworks: PyTorch, TensorFlow
• Libraries: NumPy, Pandas, Scikit-learn
• API Development: FastAPI, Flask
• Databases: SQL, NoSQL (MongoDB, Cassandra)

Cloud & Deployment

• Cloud Platforms: Azure Machine Learning, Azure Functions, Azure Databricks.
• Containerization: Docker

Required Skills

• Expertise with Pretrained LLMs, fine-tuning, RAGs, and deployment.
• Proficiency in Azure cloud environment, including model hosting and scaling.
• Advanced skills in Python, ML/DL frameworks
• Strong problem-solving, data analysis, and domain modelling capabilities.
• Demonstrated ability to mentor junior team members effectively.

Preferred Skills

• Experience with knowledge graphs, semantic search, and conversational AI.
• Familiarity with edge AI and real-time model inferencing.
• Knowledge of domain-driven design and advanced deployment strategies.
• Experience in managed service.

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