Lead ML Engineer, Performance Marketing

🔥 1 hour ago

🇺🇸 United States – Remote

💵 $164k - $205k / year

⏰ Full Time

🟠 Senior

📈 Performance Marketing

👻 Ghost score 0%

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Root Inc.

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2015

🚘 Automotive

💼 Consulting

🛡️ Insurance

💰 $200M Post IPO debt on 2024-11

Automotive • Consulting • Insurance

Root Inc. is an auto insurance company that uses a mobile app and smartphone sensor telematics to measure driving behavior and price policies primarily based on how safely customers drive. The company offers a "test drive" period to gather driving data, provides in-app quotes, policy management, and claims filing, and sells roadside assistance and other coverages across many U. S. states. Root targets consumer drivers (B2C) seeking usage-based insurance and emphasizes savings for safer drivers.

📋 Description

• Lead the design and development of production ML systems powering performance marketing optimization across channels • Architect ML solutions combining multiple models, optimization algorithms, and embedded business logic • Accelerate research-to-production through scalable infrastructure, reusable tooling, and improved 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 to enable rapid issue detection and diagnosis • Establish technical standards for maintainable, reliable ML systems and improve team development and operations • Mentor data scientists and analysts on ML systems and production engineering • Own technical direction across the ML lifecycle, from architecture and implementation through deployment and operation • Partner with data scientists, Engineering, and business stakeholders on production ML systems for performance marketing

🎯 Requirements

• 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 • 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 combining 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 ability to explain technical tradeoffs to technical and non-technical audiences • On-camera participation is required for virtual interviews • Nice to have: MS or PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field • Nice to have: Familiarity with performance marketing systems, including auction-based advertising, algorithmic bidding, or bid optimization models • Nice to have: Exposure to ML and data tooling, orchestrators, and platforms such as MLflow, Metaflow, Airflow, Dagster, Snowflake, Databricks, dbt, and Spark • Nice to have: Experience building shared ML infrastructure, developer tooling, or reusable systems that improve data science productivity • Nice to have: Fluency using generative AI and agentic tools to accelerate end-to-end ML development

🏖️ Benefits

• Bonus and LTI eligible • Work where it works best: support for working in whatever location works best across the U.S. • Reasonable accommodation during all aspects of the hiring process