Field Reliability Engineer

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

Pulled from the full job description

• Parental leave
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Health savings account
• Dental insurance, * Comprehensive medical, dental, and vision coverage
• Generous paid time off, company holidays, and parental leave
• 401(k) plan with company match (100% on the first 3% of contributions, 50% on the next 2%)
• Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA) options
• Commuter benefits (transit and parking)
• Short-term and long-term disability, and life insurance
• Employee Assistance Program (EAP) for mental health, financial, and personal support
• Onsite snacks and catered lunches

We’re building humanoid robots that work in home - doing the chores, handling the tasks, and giving people their time back. Simple, but it’s not.

To do this right, we have to solve robotics, AI, manufacturing - at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you’re inspired by this, you’ll thrive here. We’ve been at this since 2014 and we’re at the point where the hard problems are behind us and the hard work is in front of us.

NEO is our flagship - a home robot designed to move, learn, and operate in the real world alongside real people. We’re not demoing it - we’re shipping it. We’re excited to meet you, if this excites you.

If you’ve spent your career working on problems that matter and want to see them actually reach the world - this is that moment. We’re scaling, we’re hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time - safely creating abundance for all.

About the Team:

The Quality & Reliability team spans Quality, Reliability, Compliance, Failure Analysis, and Test & Validation. Together, we own ensuring 1X products are safe, reliable, compliant, and ready for customers - embedding quality systems, reliability engineering, and regulatory compliance throughout the entire product development lifecycle. Our work touches every phase of how NEO gets built and how it performs in the real world, and we hold the bar that lets the rest of the company ship with confidence.

Your Charter: Own field reliability for NEO - from surfacing emerging issues in customer and service data to leading cross-functional root cause investigations and driving verified corrective and preventative actions to closure. You are the accountability layer between what breaks in the field and what gets permanently fixed.

Key Outcomes:

• Recurring field failure rates measurably reduced through systematic CAPA closure, tracked against established baselines
• Warranty cost trajectory reported monthly with data-driven prioritization of highest-impact corrective investments
• Issue closure cycle time shortened by leading tightly scoped investigations across Hardware, Software, and AI teams
• Reliability dashboards and Nevada Charts deployed that give engineering and leadership real-time visibility into field failure rates, trends, and paretos
• Custom Python analysis tooling built that surfaces anomalies and trends from sensor telemetry faster than manual methods