Senior Databricks AI/ML Engineer

LHH is seeking a Senior Databricks AI/ML Engineer to join our client's team in a fully remote role based in Seattle, WA. Candidates must live in one of the following states, and be prepared to pass a background check/identity verification process: WA, OR, ID, OH, SC, NC, TX, or FLLHH has a dynamic and challenging opportunity for a Senior Databricks AI/ML Engineer to join our client's engineering team. This role focuses on building and deploying scalable AI/ML solutions across key areas of the insurance functions, including underwriting, claims, pricing, customer engagement, and fraud detection, with a strong emphasis on Databricks architecture and ecosystem integration. The engineer will collaborate closely with data scientists, actuaries, product owners, and engineers to operationalize models, transforming them into robust, production-grade systems seamlessly integrated into business workflows and enterprise platforms.Salary & Benefits:$150k to $185k annually (depending on location & experience)Medical, dental, and vision insurance401(k) plan with employer matchVacation time accrues at a rate of 10 days annually, with increases based on a tenure schedule, up to a maximum of 25 days per year.PTO included Four (4) personal days are granted immediately upon hire.Paid holidays are provided for the eight (8) holidays observed in this role throughout the calendar year.Up to ten (10) days of sick leave are granted immediately upon hire (pro-rated based on hire date and full-time/part-time status).Additional paid time off is available for bereavement, jury duty, and employee volunteer activities in the community.Life and disability insuranceMinimum Qualifications:Bachelor’s degree in Computer Science, AI/ML, Data Science/Engineering, or related field (or equivalent experience).6+ years experience in ETL pipelines, SQL Server, and production data workflows.3+ years enterprise experience with Azure & Databricks AI/ML, including data analysis and visual analytics.3+ years applying ML algorithms and transforming data science prototypes into production.5+ years experience with CI/CD workflows for ML models and related code.Strong SQL, real-time and batch data pipeline development, and unsupervised learning techniques.Familiarity with agile methodologies (e.g., Scrum).Responsibilities:Conduct customer workshops to gather requirements and design analytics architectures using Azure and Databricks AI/ML.Serve as Databricks Architect, managing workspace design, deployment, and governance across environments.Define and implement Databricks Lakehouse architecture and governance best practices.Integrate Databricks with Azure services and lead implementation of Databricks SQL, Delta Live Tables, and MLflow.Develop and maintain automated MLOps workflows for model deployment, monitoring, and lifecycle management.Set up and configure Azure and Databricks infrastructure for AI/ML workloads.Review ML model code and analytics scripts for quality and performance.Design and build data pipelines and cloud services for monitoring, analysis, and reporting.Develop robust ETL workflows using Databricks, Spark, and SQL Server for structured and unstructured data.Provide production support and performance tuning for data engineering workflows.Optimize complex SQL queries and stored procedures for data processing and business logic.Collaborate with cross-functional teams to ensure data quality and support business decision-making.Scale and deploy machine learning models to handle large-scale data.Feed raw data into models and build deployment pipelines for new models.Implement logging, observability, and performance monitoring for AI/ML systems.Conduct architecture reviews and performance testing.Perform other duties as assigned.Preferred Qualifications:Master’s degree in a related field.Experience in the insurance industry (Auto, Home, Umbrella) and related AI/ML applications.Proficiency with tools/platforms: Azure ML, Databricks, Microsoft Fabric, Synapse, Power BI, Snowflake, and APIs like Azure OpenAI and Cognitive Services.Knowledge of streaming frameworks: Apache Kafka, Azure Event Hubs, Delta Live Tables.Strong math, problem-solving, and rapid learning skills.Excellent communication, organization, and independent work capabilities.Service-oriented mindset with ability to handle ambiguity and build strong relationships.Equal Opportunity Employer/Veterans/DisabledTo read our Candidate Privacy Information Statement, which explains how we will use your information, please navigate to https://www.lhh.com/us/en/candidate-privacyThe Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:• The California Fair Chance Act• Los Angeles City Fair Chance Ordinance• Los Angeles County Fair Chance Ordinance for Employers• San Francisco Fair Chance Ordinance