> Markdown version of [/jobs/ext/548214-field-reliability-engineer](https://www.wearedevelopers.com/jobs/ext/548214-field-reliability-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Field Reliability Engineer - **Company:** 1X Technologies AS - **Location:** San Carlos, CA, United States - **Salary:** $94,000.0 - $115,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Failure Mode Effects Analysis, Python (Programming Language), Test Data, Large Language Models - **Published:** June 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f8a3ed308dccd65d ## About the Role Do you have experience in Statistics?, * Quantitative analyst: fluent in Weibull analysis, failure rate modeling, and statistical significance - builds the math before drawing conclusions * Systems thinker: connects sensor telemetry, software logs, and physical failure modes into a coherent root cause narrative * Cross-functional driver: creates urgency and accountability across Hardware, Software, and AI teams without direct authority * Builder: writes custom Python analysis tools and leverages LLMs to scale analytical output - doesn't wait for someone else to build the infrastructure * Clear communicator: translates complex failure data into concise reports and recommendations that land with both engineers and executives, * 1-5 years of field reliability, service engineering, or quality engineering experience in a hardware product company * Hands-on statistical failure analysis experience: Weibull modeling, failure rate prediction, FMEA * Python proficiency for data analysis and workflow automation * Bachelor's degree in Electrical Engineering, Mechanical Engineering, or closely related technical field Preferred Skills: * Experience analyzing sensor or telemetry data from electromechanical systems (robotics, automotive, consumer electronics, or similar) * Familiarity with LLMs and AI agents as analysis accelerators * Background in warranty cost modeling and financial impact reporting * Experience correlating field data with design validation and test data ## Related Videos - [Dirty Tests And How To Clean Them](https://www.wearedevelopers.com/videos/515-dirty-tests-and-how-to-clean-them) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Creating Industry ready solutions with LLM Models](https://www.wearedevelopers.com/videos/899-creating-industry-ready-solutions-with-llm-models) - [Designing UX for SRE Agents in High-Stakes Incidents](https://www.wearedevelopers.com/videos/100003-designing-ux-for-sre-agents-in-high-stakes-incidents) - [Staying Safe in the AI Future](https://www.wearedevelopers.com/videos/521-staying-safe-in-the-ai-future) - [Stop Guessing, Start Measuring: Evaluating RAG Systems with Synthetic Test Data](https://www.wearedevelopers.com/videos/1982-stop-guessing-start-measuring-evaluating-rag-systems-with-synthetic-test-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Trustworthy AI Starts at Deployment: 5 Checks Before You Ship](https://www.wearedevelopers.com/magazine/753-trustworthy-ai-starts-at-deployment-5-checks-before-you-ship) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)