Senior Staff Safety Analytics and Metrics Engineer - Robot Safety

About the role

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 Autonomy & Safety Engineering team is responsible for ensuring 1X robots operate safely, reliably, and predictably in real-world environments. We build the systems, frameworks, and operational processes that measure, validate, and continuously improve robot safety across autonomy, perception, controls, and deployment operations. Safety analytics and metrics are foundational to how we scale embodied AI systems responsibly and confidently into real homes and dynamic environments.

Your Charter

Lead the development of safety analytics infrastructure, operational metrics, and validation frameworks that measure and improve the real-world safety performance of 1X humanoid robots. This role is critical to enabling data-driven safety decisions across autonomy development, robot deployment, and operational incident analysis as 1X scales globally.

Key Outcomes

• Design and scale safety analytics systems that provide actionable visibility into robot safety performance across development, testing, and production environments
• Establish measurable safety KPIs, operational risk metrics, and validation frameworks for autonomy and robot behavior evaluation
• Build scalable tooling and data pipelines to analyze incidents, near misses, behavioral anomalies, and operational safety trends
• Partner cross-functionally with Autonomy, Controls, Data Infrastructure, Product, and Safety teams to improve safety signal quality and operational decision-making
• Improve robot safety readiness through continuous monitoring, reporting, experimentation, and safety performance analysis at fleet scale

Key Competencies

• Deep expertise in safety analytics, data systems, autonomy validation, or large-scale operational metrics infrastructure
• Strong analytical and systems-thinking mindset with the ability to translate complex technical behaviors into measurable safety insights
• Strong programming and technical problem-solving skills across distributed systems or robotics environments
• Excellent cross-functional collaboration and communication skills across engineering, operations, and leadership teams

Minimum Requirements

• 10+ years of experience in safety analytics, robotics systems, autonomous systems, data engineering, or related technical domains
• Strong experience working with large-scale data infrastructure, analytics platforms, or operational telemetry systems
• Proficiency in Python, SQL, Spark, or similar analytics and systems programming tools
• Experience designing metrics, dashboards, experimentation systems, or operational performance frameworks
• Bachelor’s degree in Computer Science, Robotics, Statistics, Engineering, Applied Mathematics, or related technical field

Preferred Skills

• Experience working with autonomous systems, robotics, AVs, industrial automation, or safety-critical systems
• Familiarity with safety standards such as ISO 13849, IEC 61508, ISO 26262, or operational risk frameworks
• Experience with telemetry systems, simulation environments, or fleet-scale robotics operations
• Experience in machine learning, anomaly detection, or statistical modeling for operational systems
• Advanced degree (MS or PhD) in Robotics, AI, Data Science, Statistics, or related field