DPSF-DPH-AI Support Engineer-Associate

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 looking for a motivated and detail-oriented AI Engineer to join our team, focusing on MLOps practices and Generative AI applications. This role is ideal for early-career professionals who are passionate about building scalable AI pipelines, deploying models in production, and exploring cutting-edge GenAI technologies.

Key Responsibilities

• Assist in designing and implementing MLOps pipelines for model training, validation, deployment, and monitoring.
• Support the development and fine-tuning of Generative AI models (e.g., LLMs, diffusion models) for internal and client-facing use cases.
• Automate data ingestion, preprocessing, and feature engineering workflows.
• Collaborate with data scientists and software engineers to operationalize AI models using CI/CD tools.
• Monitor model performance and manage versioning, rollback, and retraining strategies.
• Contribute to prompt engineering, model evaluation, and safety testing for GenAI systems.
• Document workflows, APIs, and deployment strategies for reproducibility and scalability.

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, AI/ML, or related field.
• Solid programming skills in Python and familiarity with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Basic understanding of MLOps concepts such as model lifecycle management, containerization (Docker), and orchestration (e.g., Airflow, Kubeflow).
• Exposure to Generative AI models and frameworks (e.g., Hugging Face Transformers, LangChain).
• Familiarity with Git, REST APIs, and cloud platforms (AWS, Azure, or GCP).
• Strong analytical and problem-solving skills.

Preferred Qualifications

• Internship or academic project experience in MLOps or GenAI.
• Experience with ML model deployment using FastAPI, Flask, or Streamlit.
• Knowledge of vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).
• Exposure to monitoring tools (e.g., MLflow, Prometheus, Grafana).
• Understanding of data privacy, model interpretability, and responsible AI principles.

EY | Building a better working world

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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.