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 FL
LHH 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 insurance
- 401(k) plan with employer match
- Vacation 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 insurance
Minimum 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/Disabled
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The 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
