Lead ML Engineer, Performance Marketing

At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all.

We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love.

At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all.

We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love.

The Opportunity

We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry.

At Root, the Quantitative Science team owns the majority of all marketing capital allocation, using quantitative methods to test, maintain, and enhance our marketing strategies across numerous distribution channels. As a Lead Machine Learning Engineer on the Performance Marketing team, you’ll lead the development of the ML systems that power how Root bids for, targets, and acquires customers across performance marketing channels.

You’ll work at the intersection of machine learning and engineering, translating models and optimization strategies into scalable, reliable production systems. These systems go beyond serving individual predictions, combining multiple models, optimization algorithms, and embedded business logic to make marketing decisions at scale. You’ll own technical direction across the ML lifecycle, from architecture and implementation through deployment and operation.

This role demands an ownership mentality and the ability to independently drive complex technical work, establish engineering best practices, and mentor data scientists and analysts. You’ll partner closely with data scientists, Engineering, and business stakeholders to shape how Root builds and operates production ML systems for performance marketing.

Root is a “work where it works best” company, meaning we will support you working in whatever location works best for you across the U.S.

Salary Range: $164,000 - $205,000 (Bonus and LTI eligible)

How You Will Make an Impact

• Lead the design and development of production ML systems that power performance marketing optimization across channels.
• Architect ML solutions that combine multiple models with optimization algorithms and embedded business logic.
• Accelerate the path from research to production through scalable infrastructure, reusable tooling, and better ML development practices.
• Partner with data scientists to translate new models and optimization approaches into scalable production solutions.
• Design and operate real-time ML capabilities that perform reliably under production latency constraints.
• Build monitoring and observability for interconnected ML systems, enabling rapid detection and diagnosis of issues.
• Establish technical standards for maintainable, reliable ML systems and improve how the team develops and operates them.
• Mentor data scientists and analysts on ML systems and production engineering.

What You Will Need to Succeed

• BS in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 5+ years of experience designing, building, deploying, and maintaining machine learning systems and ML model pipelines in partnership with data scientists.
• Strong Python and software engineering fundamentals, with the ability to build maintainable ML systems and production-quality code.
• Experience building and operating production ML systems, including real-time model serving, deployment, monitoring, debugging, and workflow orchestration.
• Ability to design reproducible systems with clear lineage, versioning, and operational visibility across complex ML workflows.
• Comfort working with complex ML systems that combine multiple models, optimization or search algorithms, and embedded business logic.
• Strong judgment around model evaluation, code quality, system reliability, and maintainable engineering tradeoffs.
• Working knowledge of experimentation and statistical model evaluation in production ML settings.
• Experience with cloud-based ML infrastructure and data platforms such as AWS, GCP, or Azure.
• Experience with infrastructure as code, such as Terraform.
• Clear communication skills and the ability to explain technical tradeoffs to both technical and non-technical audiences.

Nice to Have

• MS or PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Familiarity with performance marketing systems, including auction-based advertising, algorithmic bidding, or bid optimization models.
• Exposure to ML and data tooling, orchestrators, and platforms such as MLflow, Metaflow, Airflow, Dagster, Snowflake, Databricks, dbt, and Spark
• Experience building shared ML infrastructure, developer tooling, or reusable systems that improve data science productivity. 
• Fluency using generative AI and agentic tools to accelerate end-to-end ML development.

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Consistent with the Americans with Disabilities Act (ADA) and the Civil Rights Act of 1964, it is the policy of Root to provide reasonable accommodation when requested by a qualified applicant or candidate with a disability, unless such accommodation would cause an undue hardship for Root. The policy regarding requests for reasonable accommodation applies to all aspects of the hiring process. If reasonable accommodation is needed, please contact [email protected].