{"id":3358379,"url":"https://alion.io/job/ey-ai-machine-learning-engineering-consultant-databricks-manager-consulting-location-open","title":"AI & Machine Learning Engineering Consultant - Databricks - Manager - Consulting- Location OPEN","company":{"id":2859,"name":"EY","domain":"ey.com","url":"https://alion.io/company/ey-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150700,"max":251200,"currency":"USD","period":"year","gross":null,"usd_annual":251200},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AgentOps","optional":false},{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Pandas","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scala","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-10-27T20:32:17Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-31T20:39:24Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Location: Anywhere in Country\nAt EY, we’re all in to shape your future with confidence.\nWe’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.\nThe opportunity\nOur AI, Data & Engineering team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.\nEY is experiencing significant growth in consulting services centered on Databricks, a market-leading data and AI platform. We are seeking an accomplished leader who combines strong business acumen, consulting experience, and technical credibility to help clients realize value from this strategic platform. In this role, you will collaborate with clients and Databricks account, sector, and leadership teams to shape and deliver generative AI use cases, advanced data and AI solutions, and scalable platforms.\nIn this role, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems that learn, reason, and generate outputs tailored to business requirements on Databricks. You will enhance data pipelines and storage on Databricks, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions. You will deliver solutions on Databricks, from data pipelines to agents in production.\nYour key responsibilities\nAs a Manager in Model Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. 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.\nYou 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.\nYour responsibilities will include:\nLeading AI workstreams from solution design through production deployment and ongoing optimization, focusing on the Databricks platform\nLeading teams building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks\nContinuously improving processes by identifying innovative solutions through research and analysis\nManaging multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results\nEngaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure\nDesigning, building, and governing domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products\nApplying a product-centric development approach by partnering with product, business, data science, and engineering stakeholders to define user needs, prioritize reusable capabilities, and iteratively deliver measurable outcomes across the product lifecycle\nIdentifying opportunities for additional services and managing engagement economics\nSkills and attributes for success\nTo excel in this role, you will need a blend of technical expertise and strong interpersonal skills. 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\nThe following attributes will make a significant impact:\nTranslating AI strategy into a implementable Model Engineering activities that aligns with the client’s goals, mission and vision \nLeading teams of AI engineers, data engineers, and data scientists in the delivery of production-grade solutions for clients on Databricks; These include data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions\nImplementing product-centric AI solutions on Databricks, from discovery and roadmap definition through iterative delivery, adoption, and continuous improvement, with measurable business and user outcomes.\nWorking across design, build, deploy, and operate phases to deliver production-grade data and AI pipelines, governed business ontologies, and semantic models on Databricks, ensuring solutions are reliable, reusable, and aligned with client business processes\nExperience 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\nStaying 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\nApplying 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\nCollaborating with Data Scientists, Data Engineers, Cloud Engineers, and Platform Engineers, DevOps to implement and sustain solutions in the Databricks platform\nStaying abreast of industry trends, technology innovations and AI regulatory requirements across the globe\nUnderstanding clients’ overall data, AI and technology landscape and business priorities and success measures\nStrong team collaboration and experience working with a diverse team in a hybrid model (on site and remote)\nFostering relationships with client personnel at appropriate levels\nConsistently delivering quality client services\nDriving high-quality work products within expected timeframes and on budget\nCollaborating, influencing and building consensus through constructive relationships and effective listening\nSolving problems by incorporating data into decision making \nTo qualify for the role, you must have:\nA Bachelor’s degree required (4-year degree)\n6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning\n2-4 years of experience directly managing technical teams\n3-4 years of experience building and deploying production AI/ML solutions on the Databricks platform, including use of Agent Bricks, Model Serving, or Lakeflow Jobs\nDatabricks 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\nStrong skills in Python, PySpark, and/or Scala\nAbility lead, collaborate, and communicate effectively with diverse, hybrid and global teams\nExperience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform, using Databricks\nDelivered models or agents to production on Databricks, with tracking, evaluation, and monitoring\nProficient 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\nExperience with natural language processing and deep learning\nExtensive experience in DevOps tools (Git, Azure DevOps), AI-driven SDLC, and CI/CD pipelines for developing, deploying, and scaling analytical solutions on Databricks, for example with Databricks Git folders, Declarative Automation Bundles, and the Databricks CLI and SDKs\nExperience 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\nExperience with model retraining and feedback loop methodologies on Databricks, for example with Lakeflow Jobs and Databricks Feature Store\nExperience with model and solution evaluation, observability, monitoring, and reporting on Databricks, including MLflow evaluation and tracing, and data quality monitoring\nUnderstanding of data structures, data modeling, software engineering, and Responsible AI practices\nExperience designing, implementing, validating, and maintaining ontologies, taxonomies, knowledge graphs, or semantic data models in collaboration with domain experts\nExperience with product-centric development, including translating customer and business needs into product requirements, roadmaps, iterative releases, and measurable adoption or performance outcomes\nStrong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques, using Databricks tools including Databricks SQL and Delta Lake\nExcellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements\nSkills in Technical Design Optimization\nStrong relationship-building skills\nDemonstrated client trust and value\nDigital fluency and emotional agility\nCommercial acumen and negotiation skills\nProven ability to lead teams and manage change\nIdeally, you’ll also have:\nA deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them\nMaster's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field\nDatabricks Solution Architect Champion Badge preferred\nExperience working with diverse teams to deliver complex solutions\nExperience fine-tuning Generative AI models on Databricks, including with AI Runtime (serverless GPU)\nExperience in managing complex projects with multiple stakeholders\nA strong understanding of industry trends and emerging technologies\nSkills in data visualization and storytelling with data\nExperience with image processing techniques and/or speech and audio processing and analysis\nDatabricks Certifications in the 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