Lead Machine Learning Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $164.2k - $240k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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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 implementation of the long-term technical roadmap for pricing ML tools and workflows • Work with researchers to define platform needs across data readiness, feature engineering, model fitting, serving, diagnostics, and monitoring • Build feature pipelines and feature stores, reproducible model training and orchestration, model registries and versioning, automated validation, model serving, production observability, and supporting tooling • Automate end-to-end workflows using LLM technology and agentic data science workflow automation • Own execution of major platform capabilities from design through production • Break down ambiguous problems, manage dependencies, guide design decisions, and drive delivery across multiple engineers • Orchestrate the software development lifecycle across the team • Mentor and grow engineers through technical guidance and feedback • Ensure reliability, observability, reproducibility, and correctness standards across platform systems • Write and review code, drive execution, and maintain reliable production systems serving customers

🎯 Requirements

• 8+ years of software engineering experience • Demonstrated track record building and delivering production ML platforms and large-scale data processing systems • Hands-on experience with feature pipelines or feature stores, reproducible model training and orchestration, model registries and versioning, automated validation, or model serving • Strong system design and distributed systems fundamentals • Experience building reliable, scalable production services and data pipelines • Working knowledge of the ML lifecycle and engineering considerations for training, evaluating, deploying, and operating models in production • Experience designing and operating systems requiring reliability, observability, reproducibility, and correctness • Ability to take ambiguous technical initiatives, break them into executable work, manage dependencies, and drive delivery across multiple engineers • Track record working closely with Data Scientists or researchers • Experience mentoring engineers, guiding technical design, and raising engineering quality • Proficiency with Python and modern ML and data tooling • Excellent communication skills with engineers, researchers, Product, and cross-functional stakeholders • Preferred: understanding of ML models, research velocity improvements, training-serving consistency, model lineage, reproducibility, model-versioning, regulated or data-intensive environments, and LLM or agentic systems • Candidates must be on camera for virtual interviews

🏖️ Benefits

• Competitive bonus • Equity offering • Work from whatever location works best across the US • Reasonable accommodation throughout the hiring process