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

- **Company:** Ernst & Young LLP
- **Location:** St. Louis, MO, United States (Remote available)
- **Experience:** Expert
- **Salary:** $128,400.0 - $192,500.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Audio Signal Processing, Microsoft Azure, Cloud Computing, Information Engineering, Data Transformation, Data Structures, DevOps, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, Systems Development Life Cycle, Search Technologies, Software Construction, Software Engineering, SQL Databases, Enterprise Data Management, Feature Store, Cloud Platform System, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Deep Learning, Generative AI, Agentic-AI, Git, Pandas, Data Lakes, Pyspark, Scikit Learn, Information Technology, AgentOps, Machine Learning Operations, AIOps, Serverless Computing, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3479355218&tx=CT3432TYD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry., To excel in this role, you will need a blend of technical expertise and interpersonal skills. Your ability to navigate complex challenges and deliver impactful solutions will be essential., 1. A Bachelor's degree required (4-year degree).

 2. 3-6 years of full-time working experience in AI and/or Machine Learning
 3. Databricks Certification with a minimum of 1 professional and 1 associate certification that includes a combination of Data Engineer Associate or Professional, Machine Learning Associate or Professional, Generative AI Engineer Associate, and/or Context Engineering Associate
 4. Strong skills in Python, PySpark, and/or Scala
 5. Ability to collaborate and communicate effectively with diverse, hybrid, and global teams.
 6. Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform using Databricks
 7. 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.
 8. Delivered models or agents to production on Databricks, with tracking, evaluation, and monitoring.
 9. Proficient in foundation models, generative AI, and agentic AI frameworks (e.g., Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch, using Databricks tools including Agent Bricks, AI Search, Foundation Model APIs, and Unity Gateway
 10. Experience with natural language processing and deep learning
 11. Extensive experience in DevOps tools (Git, Azure DevOps) and AI-driven SDLC for developing, deploying, and scaling analytical solutions on Databricks, for example with Databricks Git folders, Declarative Automation Bundles, and the Databricks CLI and SDKs
 12. Experience with MLOps, LLMOps, and AgentOps and ML workflows on Databricks, including data ingestion, transformation, and evaluation, for example with MLflow, Models in Unity Catalog, and Model Serving
 13. Experience with model retraining and feedback loop methodologies on Databricks, for example with Lakeflow Jobs and Databricks Feature Store
 14. Experience evaluating and operating models and AI solutions on Databricks, including observability, monitoring, reporting, MLflow evaluation and tracing, and data quality monitoring.
 15. Understanding of data structures, Responsible AI practices, and data modelling, and software engineering best practices
 16. Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques, using Databricks tools such as Databricks SQL and Delta Lake, using Databricks tools such as Databricks SQL and Delta Lake.
 17. Excellent communication skills for conveying findings and recommendations, with willingness to travel as needed for client engagements.

Ideally, you'll also have:

 * Master's degree Computer Science, Mathematics, Physical Sciences, or another quantitative field
 * Databricks Solution Architect Champion Badge preferred
 * Experience in hybrid collaboration and emotional agility
 * A track record of working with diverse teams to drive outcomes through complex problem-solving 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 to apply them
 * 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

What we look for

We seek individuals who are not only technically proficient but also possess the qualities of a top performer. You should be innovative, adaptable, and purpose driven by a desire to make a significant impact in the field of artificial intelligence. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.

## Description

In this role, you will contribute significantly to the delivery of innovative AI solutions. You will work with a wide variety of clients to deliver modern AI engineering, machine learning, and generative AI technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure AI solutions are responsibly engineered, evaluated, deployed, and maintained to support the ongoing business needs of our clients., * Researching and implementing scalable machine learning, generative AI, and agentic systems that meet business requirements

 * Building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks
 * Evaluating, monitoring, and optimizing learning processes on Databricks to improve high-performance models, with tools like MLflow evaluation and tracing
 * Designing, building, and governing domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products
 * This position may have travel requirements as needed to engage with external clients regularly, This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services.
 * Translating AI strategy into a implementable Model Engineering activities that aligns with the client's goals, mission and vision
 * Working 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-for clients on Databricks
 * Implementing product-centric AI solutions on Databricks, from discovery and roadmap definition through iterative delivery, adoption, and continuous improvement, with measurable business and user outcomes
 * Working across design, build, deploy, and operate phases to deliver production-grade data and AI pipelines, including governed business ontologies and semantic models on Databricks, so solutions remain reliable, reusable, and aligned with client business processes
 * Applying a product-centric development approach to data and AI solutions 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
 * Staying abreast of AI technology trends and provide directional guidance and recommendations around AIOps, MLOps, and AgentOps tools and solutions on Databricks that fit their needs and integrate with their existing ecosystem
 * Applying combined business and technical knowledge to develop and execute ModelOps target architecture on Databricks that enables implementation and monitoring of AI at scale, with tools like Unity Catalog and Model Serving
 * Collaborating with Data Scientists, Data Engineers, Cloud Engineers, and Platform Engineers, DevOps to implement and sustain solutions in the Databricks platform
 * Understanding clients' overall data, AI and technology landscape and business priorities and success measures
 * Strong team collaboration and experience working with a diverse team in a hybrid model (on site and remote)
 * Working on large-scale client engagements. Fostering relationships with client personnel at appropriate levels. Consistently delivering quality client services. Driving high-quality work products within expected timeframes and on budget
 * Collaborating, influencing and building consensus through constructive relationships and effective listening
 * Solving problems by incorporating data into decision making