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Rapsodo

Provides data-driven performance analysis for athletes

Device Quality Engineering Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSingapore$1In-person

About the Job

Requirements

  • Typically 8+ years in embedded or connected-device validation, systems test, integration or quality engineering, including technical leadership and experience shipping products.
  • Demonstrated hands-on ownership of a hardware-in-the-loop farm or automated hardware-test system, including fixtures, instrument control, device recovery and reliable continuous integration execution.
  • Strong Python automation and embedded Linux debugging skills; comfortable reading C/C++ and investigating failures through logs, traces, application programming interfaces and laboratory instruments.
  • Experience designing end-to-end, performance, reliability and interruption/recovery tests, and separating device, firmware, algorithm, application and test-infrastructure failure modes.
  • Sound judgement in measurement uncertainty, repeatability, test coverage and release evidence, supported by experience mentoring engineers.
  • A relevant engineering degree or equivalent practical experience.

Responsibilities

  • Define risk-based validation plans from early development through release and sustaining, working with engineering owners to establish measurable acceptance criteria.
  • Maintain coverage across supported hardware, firmware, model and application combinations; prioritise critical customer workflows, technical risks and field issues.
  • Assess existing tests and lab capability, establish coverage and reliability baselines, and build a prioritised cross-product test roadmap.
  • Own test architecture, device inventory, fixtures, remote access, scheduling and reliable unattended execution across the hardware-in-the-loop farm.
  • Automate provisioning, firmware flashing, power cycling, USB/network control, device recovery and capture of diagnostic logs and test artifacts.
  • Establish rig-health checks, reference calibration, safe operation and maintenance; distinguish product defects from rig failures and resolve unreliable tests.
  • Personally design, code, review and debug reusable test frameworks integrated with continuous integration/continuous delivery, including fast change-level checks, nightly regression and release-candidate testing.
  • Validate setup, connectivity, sensor capture, synchronisation, computation, measurement delivery and session persistence, including device-to-app and service boundaries.
  • Exercise firmware updates, interruption and recovery, repeated sessions, connectivity loss, long-running operation and relevant power or resource stress.
  • Partner with Architecture, computer vision/image processing and hardware specialists on reference measurements, tolerances, sample needs and representative operating-envelope coverage.
  • Govern versioned Golden Dataset regression, keep validation data separate from algorithm-tuning data, and trace results to hardware, firmware, model, calibration and test conditions.
  • Keep data replay, real-device hardware-in-the-loop and physical sensor tests distinct. Coordinate indoor/outdoor, equipment, positioning, temperature and endurance testing with the relevant specialists.
  • Maintain requirement-to-test traceability and configuration-specific evidence, clearly distinguishing passed, failed, untested and invalid results.
  • Publish automated quality views covering critical coverage, actionable regression feedback, flaky or invalid runs, unresolved validation gaps and residual risks.
  • Withhold quality sign-off when required evidence or acceptance criteria are unmet, and escalate to the Head of RDO. Final release decisions follow the approved policy; non-waivable requirements remain blockers.
  • Lead and develop two engineers while remaining a substantial hands-on contributor; own the automation backlog, review test code and coordinate shared lab capacity.
  • Partner with Product Leads, Support and engineering owners to reproduce field issues, improve diagnostics, verify fixes and add regression tests or other prevention controls.
  • Make coverage gaps and resource constraints visible early. Product and functional teams retain responsibility for design quality, unit/subsystem testing and defect correction.

Desired Qualifications

  • Camera/radar, imaging, robotics, computer vision, calibration or sports-measurement experience is valuable.
  • Familiarity with continuous integration/continuous delivery, test-result management, field diagnostics and environmental qualification is an advantage.

About the Company

Rapsodo

Provides data-driven performance analysis for athletes

Rapsodo makes sensor-based performance measurement devices for golf, baseball, and softball, paired with data-driven software for athletes and coaches. The hardware uses doppler radar and cameras to measure metrics like ball speed, club speed, launch angle, distance, velocity, and spin rate, then streams data to mobile and web apps with video playback and shot tracing. It differentiates itself by combining multi-sport hardware with cloud and app analytics and a global presence, serving amateurs to professional teams and colleges. Its goal is to help athletes and coaches improve performance through precise data and actionable insights.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Singapore
Founded
2010

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