Battery Test Engineer (Robotics)

1X Technologies AS•San Carlos, CA

21h•$106,400 - $146,300

About The Position

You will work hands-on with cells, packs, and complete robotic battery systems, generating high-quality data that directly informs battery algorithms, hardware design, and system-level energy management.

Requirements

Education: BS/MS in Electrical Engineering, Mechanical Engineering, Energy Systems, or related field.
Experience: 2+ years in battery testing, validation, or reliability engineering (cells, modules, or packs).
Hands-on experience with lithium-ion batteries and test equipment.
Strong understanding of battery performance metrics, degradation mechanisms, and safety risks.
Experience with data analysis using Python, MATLAB, or similar tools.
Comfortable working in lab environments and following strict safety protocols.

Nice To Haves

Experience testing batteries for robotics, automotive, aerospace, or other high-reliability systems.
Familiarity with BMS architectures and battery algorithms.
Experience with automated test frameworks and scripting.
Knowledge of relevant standards (UN38.3, IEC 62133, UL, ISO 26262).
Experience working with environmental, thermal, or vibration testing.

Responsibilities

Plan and execute battery test campaigns for cells and packs used in robotic platforms.
Design test procedures for performance, aging, safety, and abuse testing under robotics-relevant load profiles.
Operate battery cyclers, environmental chambers, and thermal test equipment.
Develop robotic-duty-cycle test profiles reflecting real-world use (high transients, intermittent loads, regen events).
Collect, validate, and analyze test data; identify anomalies and failure modes.
Collaborate closely with battery algorithm, hardware, firmware, and robotics teams to support model development and validation.
Support BMS validation including SoC/SoH accuracy, fault detection, and protection thresholds.
Maintain test hardware, fixtures, wiring, and safety procedures.
Document test results, methodologies, and recommendations clearly and rigorously.
Support root-cause analysis of field issues and fleet data findings.