Lead Machine Learning Engineer I, Lifetime Value

Root is on a mission to improve insurance through innovative data and technology, focusing on reimagining insurance to be smarter, more equitable, and customer-centric. They emphasize research, experimentation, and data-driven decision making to build beloved products.

Location: Remote (US)

Salary: $164,000 - $205,000 (Eligible for Bonus & Equity)

Responsibilities

• Build and improve systems powering customer lifetime value modeling from development to monitoring and support.
• Partner with data scientists to productionize models, simulations, and forecasts supporting decision-making.
• Accelerate research-to-production with scalable infrastructure, workflows, and tooling.
• Enhance ML development experience through operational patterns and production practices.
• Develop tools for stakeholders to evaluate model performance, understand impact, and trust outputs.
• Collaborate to solve high-value problems and improve ML system reliability and scalability.
• Share best practices via mentorship, documentation, and communication.

Requirements

• BS in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 5+ years of experience in designing, deploying, and maintaining ML systems and pipelines.
• Strong Python and software engineering skills for maintainable, production-quality code.
• Experience with deploying, monitoring, debugging, and orchestrating ML systems.
• Ability to design reproducible systems with clear lineage, versioning, and operational visibility.
• Comfort working with interconnected ML components, simulation logic, and business rules.
• Strong judgment on model evaluation, code quality, reliability, and engineering tradeoffs.
• Experience with cloud ML infrastructure (AWS, GCP, Azure).
• Experience with infrastructure as code (Terraform).
• Excellent communication skills for technical and non-technical audiences.

Benefits

• Competitive bonus and equity.
• Flexible work location across the U.S.

Additional Information

• Candidates must be on camera for interviews.
• See privacy notice for data processing details.
• Reasonable accommodations available for applicants with disabilities.