Staff Machine Learning Engineer

🕒 September 1

🇺🇸 United States – Remote

💵 $188.8k - $265k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 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

• Define the long-term technical roadmap for pricing innovation through ML tools and workflows • Work with researchers to improve R&D workflows from data readiness through feature engineering, model fitting, serving, diagnostics, and monitoring • Define architecture and versioned contracts connecting data, features, models, and production pricing • Automate end-to-end workflows using LLM technology for agentic data science workflow automation • Write and review code in critical platform components • Drive technical design across systems and cross-team dependencies • Mentor senior engineers in architecture, platform design, and ML engineering best practices • Set standards for reliability, observability, reproducibility, and correctness • Own long-term architectural design, platform technical strategy, and technical coherence over time • Collaborate across platform teams, Data Science, and Actuarial

🎯 Requirements

• 10+ years of software engineering experience • Track record designing and delivering business-critical ML platforms, data platforms, or similarly complex distributed systems • Architectural ownership of production ML infrastructure, including feature pipelines/stores, model training and orchestration, model registries and versioning, model serving, or research-to-production infrastructure • Strong system design and distributed systems expertise • Experience designing reliable, scalable data processing systems and well-defined interfaces between complex systems • Experience with reproducibility, lineage, versioning, training-serving consistency, and production correctness • Working knowledge of the ML lifecycle and engineering considerations for training, evaluating, deploying, and operating production models • Ability to establish technical direction in ambiguous problem spaces and translate architectural goals into executable plans • Track record creating technical leverage across multiple teams through shared platforms, abstractions, standards, or tooling • Ability to influence technical direction across teams without direct authority and mentor senior engineers • Experience collaborating with Data Scientists and researchers • Proficiency with Python and modern ML and data tooling • Excellent written and verbal communication skills • Preferred: understanding of ML and statistical modeling, common ML algorithms/frameworks, model development velocity, regulated or data-intensive domains, quantitative-research platforms, and LLMs or agentic systems

🏖️ Benefits

• Eligible for competitive bonus • Equity offering • Work in whatever location works best for you across the US • Reasonable accommodation throughout the hiring process