Site Reliability Engineer, Optimus

As a Telemetry Engineer on the Optimus team, you will be responsible for monitoring and reporting on fleet-wide performance metrics, uptime, and serviceability across our humanoid robot platform. You'll develop and integrate processes, tools, and automation pipelines to monitor and ensure optimal performance of robots in the field — turning raw telemetry into actionable engineering decisions. This role sits at the intersection of data engineering, reliability engineering, and robotics. You'll lead technical discussions on fleet health and analytics, collaborating with hardware, firmware, manufacturing, and service teams to drive measurable improvements in uptime and reliability. An ideal candidate combines strong data fundamentals (SQL, Python, large-scale analytics) with a self-starter mentality and the ability to thrive in a fast-moving, high-ambiguity environment.

Responsibilities

Perform detailed reviews of fleet performance, identifying common failure modes, sources of downtime, and reliability trends across the robot fleet Develop and execute cross-team strategies to resolve recurring issues and improve fleet reliability, serviceability, and uptime Use SQL and Python to extract, organize, and analyze telemetry from a variety of sources, surfacing actionable insights on fleet performance and failure trends Build and maintain reporting systems — dashboards, automated reports, and executive-ready presentations — that communicate robot performance and operational trends clearly Partner with engineering and operations teams to design tools and pipelines that scale fleet analytics as the robot population grows Correlate field telemetry with manufacturing test data, HIL testing results, and firmware releases to identify root causes and validate fixes Participate in an on-call rotation to triage critical fleet incidents as needed

Requirements

Bachelor's Degree in Computer Science, Engineering, Physics, Math, or equivalent demonstrated skills, or equivalent experience 2+ years of experience in data engineering, telemetry, reliability, or fleet analytics (or equivalent) Strong proficiency in Python (Pandas, NumPy) and SQL (PostgreSQL, ClickHouse, or similar) Experience working with large-scale datasets and building reproducible analysis pipelines Excellent written and verbal communication; ability to translate complex findings into executive-ready summaries Self-starter mentality with a proven track record of identifying problems and driving them to resolution in ambiguous environments