AI & Machine Learning Engineering Consultant - Databricks - Senior - Consulting - Location OPEN
Ernst and Young3 days ago
Base Salary
$107k - $201k/yr
Responsibilities
- Research and implement scalable machine learning, generative AI, and agentic systems on Databricks.
- Build data engineering pipelines and production AI solutions from data ingestion through deployment and operation.
- Evaluate, monitor, optimize, and retrain models and AI solutions using model tracking, evaluation, observability, and feedback loops.
- Design, build, and govern domain ontologies, semantic models, knowledge graphs, and enterprise data products.
- Develop and execute ModelOps target architectures using tools such as Unity Catalog and Model Serving.
- Provide technical guidance, collaborate with multidisciplinary and client teams, and translate AI strategy into implementable engineering work.
- Apply product-centric practices including roadmap and backlog management, user feedback, adoption measurement, and continuous improvement.
- Advise clients on AIOps, MLOps, AgentOps, and Databricks solutions across discovery, build, deployment, and operation phases.
- Deliver high-quality client work products within expected timeframes and budgets, with travel as needed.
Requirements
- Bachelor’s degree required; a master’s degree in computer science, mathematics, physical sciences, or another quantitative field is preferred.
- 3–6 years of full-time experience in AI and/or machine learning, including at least two years building and deploying production AI/ML solutions on Databricks.
- At least one Databricks professional certification and one Databricks associate certification from the specified data engineering, machine learning, generative AI, or context engineering certifications.
- Strong skills in Python, PySpark, and/or Scala.
- Experience designing, building, maintaining, evaluating, monitoring, and operating production AI/ML solutions on a major cloud platform using Databricks.
- Experience with Agent Bricks, Model Serving, Lakeflow Jobs, foundation models, generative AI, agentic AI, RAG, natural language processing, deep learning, scikit-learn, and PyTorch.
- Experience with Databricks AI Search, Foundation Model APIs, Unity Gateway, MLflow, Models in Unity Catalog, Databricks Feature Store, Databricks SQL, and Delta Lake.
- Experience with Git, Azure DevOps, Databricks Git folders, Declarative Automation Bundles, the Databricks CLI, and Databricks SDKs.
- Experience with MLOps, LLMOps, AgentOps, data ingestion and transformation, model retraining, evaluation, observability, reporting, and data quality monitoring.
- Understanding of data structures, responsible AI, data modeling, software engineering best practices, mathematics, statistics, operations research, SQL, Pandas, and Spark.
- Strong communication, collaboration, problem-solving, and client engagement skills, with willingness to travel.
- Preferred qualifications include a Databricks Solution Architect Champion Badge, fine-tuning generative AI models with AI Runtime, image processing, and speech or audio processing experience.
Benefits
- Medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
- Location-open within the country, with hybrid on-site and remote collaboration and travel as needed for client engagements.
- EY provides professional growth opportunities, personal fulfillment, and an inclusive culture.
Tech Stack
Categories
ML EngineeringSolutions Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.