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Ernst & Young

Global professional services: consulting, assurance, tax

EY-Parthenon - Strategy and Execution, Growth Platforms, AI ML Engineering, Director

Applied Machine LearningUpdated on Nov 14
Full-timeNew York, NY, USA$205k - $235k

About the Job

Requirements

  • A bachelor's degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or another related field and five years of related work experience; or a graduate degree and approximately three years of related work experience.
  • Full-time, hands-on experience applying artificial intelligence and machine learning to solve real-world problems.
  • Familiarity with multimodal agent frameworks such as LangChain, Haystack, and retrieval-augmented generation pipelines.
  • Expertise in vector databases such as Pinecone, Weaviate, and Chroma, retrieval systems, and large language model fine-tuning.
  • Strong understanding of real-world structured data merging, schema linking, and model evaluation at scale.
  • Strong understanding of machine learning workflows, including ingesting, analyzing, and transforming data, and evaluating results to make meaningful predictions.
  • Fluency in Python and PyTorch or TensorFlow, with the ability to architect application programming interfaces around machine learning models.
  • Proven experience designing, building, and maintaining machine learning models, frameworks, and pipelines.
  • Experience working with and/or leading cross-functional business and engineering teams to deliver complex solutions.
  • Ability to convey complex technical concepts and progress, methodologies, solutioning, and results to business and client stakeholders.
  • Ability and willingness to travel and work beyond standard hours when necessary.

Responsibilities

  • Partner with business and strategy leads to translate business needs into executable artificial intelligence workflows, data pipelines, and client-specific product specifications.
  • Define end-to-end architecture for agents integrating large language models, retrieval-augmented generation, multi-source data ingestion, and analytics components.
  • Lead model selection, feature design, embedding strategy, and prompt frameworks such as LangChain and LlamaIndex.
  • Design and build robust, scalable, reproducible, and versioned data pipelines.
  • Collaborate with data engineering and DevOps on pipeline integration, data normalization, and system deployment.
  • Set coding standards and mentor junior engineers; perform model and code reviews and refine level of effort, scope, and roadmaps.
  • Own delivery of artificial-intelligence- and machine-learning-powered components from prototype to production, including REST APIs, dashboards, or embedded agents.
  • Build and maintain the core advanced analytics platform and serve as the technical execution lead for high-visibility client engagements.
  • Work with business leaders and C-level executives to translate business needs into technically executable machine-learning agentic workflows and guide a team of engineers and contractors through end-to-end project lifecycles.

Desired Qualifications

  • Experience building and deploying artificial-intelligence or machine-learning products or features in a production environment.
  • Experience working in a startup and/or in management or strategy consulting.
  • Knowledge of leveraging artificial-intelligence tools in a business setting, including Microsoft Copilot.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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