GMS - GST-Data Scientist AI Engineer-Senior

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

Role Overview
We are seeking an experienced AI Engineer / Data Scientist to lead asset development, data science product building, and rapid prototyping. This role focuses on leveraging LLMs, ML/DL techniques, and Azure cloud to deliver scalable, impactful solutions. You will play a pivotal role in problem formulation, data analysis, solution design, and mentoring junior team members.

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.

EY | Building a better working world 

 
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.  

 
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.  

 
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.