Staff Machine Learning Engineer, Pricing Platform
Root Insurance2 months ago
Remote, United StatesStaff+
Base Salary
$189k - $265k/yr
Responsibilities
- Define the long-term technical roadmap for ML tools and workflows supporting the end-to-end pricing R&D process.
- Collaborate with researchers on data readiness, feature engineering, model fitting, serving, diagnostics, and monitoring needs.
- Design architecture and versioned contracts connecting data, features, models, and production pricing.
- Automate end-to-end workflows, including agentic data science workflow automation using LLM technology.
- Write and review code in critical platform components and drive technical design across systems and cross-team dependencies.
- Mentor senior engineers on architecture, platform design, and engineering best practices.
- Establish standards for reliability, observability, reproducibility, and correctness across platform systems.
Requirements
- 10+ years of software engineering experience designing and delivering business-critical ML platforms, data platforms, or similarly complex distributed systems.
- Demonstrated architectural ownership of production ML infrastructure such as feature pipelines or stores, model training and orchestration, model registries and versioning, model serving, or research-to-production infrastructure.
- Strong system design and distributed systems expertise, including reliable and scalable data processing systems and well-defined interfaces.
- Experience designing for reproducibility, lineage, versioning, training-serving consistency, and production correctness.
- Working knowledge of the ML lifecycle, including training, evaluation, deployment, and operating models in production.
- Ability to establish technical direction in ambiguous spaces and turn architectural goals into executable plans.
- Experience creating technical leverage across multiple teams through platforms, abstractions, standards, or tooling.
- Ability to influence across teams without direct authority and mentor senior engineers in architecture and system design.
- Experience collaborating with Data Scientists and researchers to translate research workflows into scalable platform capabilities.
- Proficiency with Python and modern ML and data tooling.
- Excellent written and verbal communication across Engineering, Data Science, Product, and leadership.
- Preferred: understanding of ML and statistical modeling, including model assumptions, bias and variance, uncertainty, evaluation methodology, and model failure modes.
- Preferred: understanding of ML algorithms and frameworks and their implications for production system design.
- Preferred: experience improving model development velocity, experimentation throughput, deployment reliability, or model quality through ML-platform investments.
- Preferred: experience building ML infrastructure in regulated or data-intensive domains such as insurance, fintech, financial services, or healthcare.
- Preferred: experience designing platforms for quantitative researchers or Data Scientists with demanding experimentation and reproducibility requirements.
- Preferred: experience applying LLMs or agentic systems to developer tooling, research workflows, or data science automation.
Benefits
- Salary range of $188,800-$265,000, plus eligibility for a competitive bonus and equity offering.
- Work-from-anywhere arrangement within the United States under Root’s “work where it works best” policy.
- Virtual interviews require candidates to be on camera, with reasonable accommodation available for qualified applicants with disabilities.
Tech Stack
Categories
About Root Insurance
Root Insurance is a publicly traded auto insurer that sells policies directly to U.S. drivers through a mobile app and website. It prices risk using smartphone-based telematics and machine-learning models, and manages end-to-end underwriting and claims. Founded in 2015 and headquartered in Columbus, Ohio, Root is listed on Nasdaq under the ticker ROOT and operates across multiple U.S. states.