Databricks AI/ML Solutions Lead

EY; Olympia (WA); Hybrid; USD 151,000 - 251,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off options

Job summary

EY seeks a Manager in Model Engineering within our AI, Data & Engineering team, combining business acumen with technical credibility to deliver scalable Databricks-based AI solutions for clients. You will lead diverse teams, build data pipelines and AI systems, and collaborate with clients in a hybrid on-site/remote model across the US, applying responsible deployment practices and measuring value.

This role offers exposure to cutting-edge generative AI, MLOps, and Ontology work, with a clear

Qualifications

• Bachelor’s degree required (4-year degree).
• 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
• 2-4 years of experience directly managing technical teams
• 3-4 years of experience building and deploying production AI/ML solutions on the Databricks platform, including use of Agent Bricks, Model Serving, or Lakeflow Jobs
• 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
• Strong skills in Python, PySpark, and/or Scala
• Ability lead, 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
• Delivered models or agents to production on Databricks, with tracking, evaluation, and monitoring
• 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
• Experience with natural language processing and deep learning
• Extensive 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
• 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
• Experience with model retraining and feedback loop methodologies on Databricks, for example with Lakeflow Jobs and Databricks Feature Store
• Experience with model and solution evaluation, observability, monitoring, and reporting on Databricks, including MLflow evaluation and tracing, and data quality monitoring
• Understanding of data structures, data modeling, software engineering, and Responsible AI practices
• Experience designing, implementing, validating, and maintaining ontologies, taxonomies, knowledge graphs, or semantic data models in collaboration with domain experts
• Experience with product-centric development, including translating customer and business needs into product requirements, roadmaps, iterative releases, and measurable adoption or performance outcomes
• Strong 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
• Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
• Skills in Technical Design Optimization
• Strong relationship-building skills
• Demonstrated client trust and value
• Digital fluency and emotional agility
• Commercial acumen and negotiation skills
• Proven ability to lead teams and manage change

Responsibilities

• Leading AI workstreams from solution design through production deployment and ongoing optimization, focusing on the Databricks platform
• Leading teams building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks
• Continuously improving processes by identifying innovative solutions through research and analysis
• Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results
• Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure
• 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
• Applying 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
• Identifying opportunities for additional services and managing engagement economics

Skills

Python

PySpark

Scala

Databricks

MLOps

AgentOps

NLP

Deep learning

Data pipelines

Education

Bachelor’s degree

Tools

Databricks

Unity Catalog

MLflow

Git

Azure DevOps

Model Serving

Job description

EY seeks a Manager in Model Engineering within our AI, Data & Engineering team, combining business acumen with technical credibility to deliver scalable Databricks-based AI solutions for clients. You will lead diverse teams, build data pipelines and AI systems, and collaborate with clients in a hybrid on-site/remote model across the US, applying responsible deployment practices and measuring value.

This role offers exposure to cutting-edge generative AI, MLOps, and Ontology work, with a clear