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Ernst & Young

Global professional services: consulting, assurance, tax

AI & Machine Learning Engineering Consultant – Senior - Databricks, Consulting, Location OPEN

Applied Machine LearningUpdated on Nov 14
Full-timeRemote in USA$106.9k - $200.6k

About the Job

Requirements

  • A four-year bachelor's degree is required.
  • Three to six years of full-time work experience in AI and/or machine learning.
  • At least one Databricks professional certification and one associate certification, with the combination drawn from Data Engineer Associate or Professional, Machine Learning Associate or Professional, Generative AI Engineer Associate, and/or Context Engineering Associate.
  • Strong skills in Python, PySpark, and/or Scala.
  • Ability to collaborate and communicate effectively with diverse, hybrid, and global teams.
  • Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform using Databricks.
  • At least two years of experience building and deploying production AI/ML solutions on Databricks, including experience with Agent Bricks, Model Serving, or Lakeflow Jobs.
  • Experience delivering models or agents to production on Databricks with tracking, evaluation, and monitoring.
  • Proficiency in foundation models, generative AI, and agentic AI frameworks such as Retrieval Augmented Generation, and experience with machine-learning packages such as scikit-learn and PyTorch, using Databricks tools including Agent Bricks, AI Search, Foundation Model APIs, and Unity Gateway.
  • Experience with natural language processing and deep learning.
  • Extensive experience with DevOps tools such as Git and Azure DevOps, and AI-driven software development life cycle practices for developing, deploying, and scaling analytical solutions on Databricks, including Databricks Git folders, Declarative Automation Bundles, and the Databricks CLI and SDKs.
  • Experience with MLOps, LLMOps, AgentOps, and machine-learning workflows on Databricks, including data ingestion, transformation, and evaluation using tools such as MLflow, Models in Unity Catalog, and Model Serving.
  • Experience with model retraining and feedback-loop methodologies on Databricks, such as Lakeflow Jobs and Databricks Feature Store.
  • Experience evaluating and operating models and AI solutions on Databricks, including observability, monitoring, reporting, MLflow evaluation and tracing, and data-quality monitoring.
  • Understanding of data structures, Responsible AI practices, data modelling, and software-engineering best practices.
  • A strong foundation in mathematics, statistics, and operations research, and proficiency with data-manipulation tools including SQL, Pandas, and Spark, as well as deep-learning techniques and Databricks SQL and Delta Lake.
  • Excellent communication skills for conveying findings and recommendations, and willingness to travel as needed for client engagements.

Responsibilities

  • Research and implement scalable machine-learning, generative-AI, and agentic systems that meet business requirements.
  • Build data-engineering pipelines and AI solutions—including machine-learning, generative-AI, and agentic-AI solutions—and their supporting pipelines on Databricks.
  • Evaluate, monitor, and optimize learning processes on Databricks to improve high-performance models, using tools such as MLflow evaluation and tracing.
  • Design, build, and govern domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products.
  • Engage with external clients regularly as needed; the position may require travel.
  • Translate AI strategy into implementable model-engineering activities aligned with client goals, mission, and vision.
  • Work with teams of AI engineers, data engineers, and data scientists to deliver production-grade data-engineering pipelines and AI solutions—including machine-learning, generative-AI, and agentic-AI solutions—for clients on Databricks.
  • Implement product-centric AI solutions on Databricks, from discovery and roadmap definition through iterative delivery, adoption, and continuous improvement, with measurable business and user outcomes.
  • Work across design, build, deploy, and operate phases to deliver production-grade data and AI pipelines, including governed business ontologies and semantic models on Databricks, keeping solutions reliable, reusable, and aligned with client business processes.
  • Apply a product-centric development approach by defining user outcomes, prioritizing reusable capabilities, managing roadmaps and backlogs, incorporating user feedback, measuring adoption and business value, and continuously improving products after launch.
  • Stay abreast of AI technology trends and provide directional guidance and recommendations on AIOps, MLOps, and AgentOps tools and solutions on Databricks that fit client needs and integrate with their existing ecosystems.
  • Apply combined business and technical knowledge to develop and execute a ModelOps target architecture on Databricks that enables implementation and monitoring of AI at scale, using tools such as Unity Catalog and Model Serving.
  • Collaborate with data scientists, data engineers, cloud engineers, platform engineers, and DevOps teams to implement and sustain solutions in the Databricks platform.
  • Understand clients’ overall data, AI, and technology landscapes, business priorities, and success measures.
  • Provide technical guidance and share knowledge with team members who have diverse skills and backgrounds.
  • Deliver quality client services on complex, judgmental, and specialized emerging-technology issues; demonstrate technical capabilities and professional knowledge; learn about EY and its service lines; and present ways to apply knowledge and services.
  • Work on large-scale client engagements, foster relationships with client personnel at appropriate levels, deliver quality client services, and drive high-quality work products within expected timeframes and budgets.
  • Collaborate, influence, and build consensus through constructive relationships and effective listening.
  • Solve problems by incorporating data into decision-making.

Desired Qualifications

  • A master's degree in Computer Science, Mathematics, Physical Sciences, or another quantitative field.
  • Databricks Solution Architect Champion Badge.
  • Experience in hybrid collaboration and emotional agility.
  • A track record of working with diverse teams to drive outcomes through complex problem-solving.
  • Knowledge of sustainability practices in technology.
  • A deep understanding of, and ability to teach, concepts, tools, features, functions, and benefits of different approaches.
  • Experience fine-tuning generative-AI models on Databricks, including with AI Runtime (serverless GPU).
  • Experience with image-processing techniques and/or speech and audio processing and analysis.

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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