Linux Sensors Lead

0 years

3 - 5 Lacs

Posted:2 weeks ago| Platform: GlassDoor logo

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Work Mode

On-site

Job Type

Part Time

Job Description

Job Requirements

____________________________________________________________________________

Key Responsibilities

  • Perform validation and characterization of sensor subsystem components:

  • Accelerometer

  • Gyroscope

  • Magnetometer

  • Barometer

  • Proximity / Light

  • Sensor fusion (6-axis / 9-axis)

  • Context detection (pedometer, activity recognition)

  • Always-On DSP (SLPI/QDSP6)

  • Validate the complete sensor pipeline across:

  • Linux/Android sensor framework

  • Sensors HAL

  • CHRE

  • DSP firmware

  • SMD/SMGR interactions

  • Execute tests for:

  • Calibration accuracy

  • Drift, noise and bias

  • Responsiveness, sampling rate stability

  • Latency/jitter

  • Power/thermal behavior

  • Concurrency and stress

  • Debug and analyze issues using:

  • logcat, bugreport

  • QXDM/QDSS

  • Sensors Diag tools

  • perfetto/systrace

  • Work with HW/FW teams to provide actionable root-cause analysis for sensor data issues.

  • Validate Android sensor APIs, HAL behaviors, and custom OEM use cases.

  • Use automation tools (Python, adb, sensor-test frameworks) for regression and continuous validation.

  • Support sensor validation during BSP bring-up, OEM integration, and feature commercialization.


Work Experience

  • Strong understanding of:

    • Sensor fundamentals (noise, drift, bias, sensitivity)

    • Sensor fusion algorithms (Kalman filter, quaternion, AHRS)

    • Android sensor framework & HAL architecture

    • DSP-side sensor processing (SLPI/QDSP6)

    • Experience with:

    • Sensor logging/debug tools

    • Characterization methods

    • Automated test execution (Python)

    • ADB/Android internals

  • Ability to analyze complex system interactions (Sensors + Location + Camera + Display).


Good to Have

  • Experience with CHRE (Context Hub Runtime Environment).

  • Knowledge of low-power architectures and Always-On sensing.

  • Familiarity with Machine Learning-based activity recognition.

  • Exposure to:

  • Location fusion (GNSS + sensors)

  • AR/VR use cases

  • Navigation-grade sensor accuracy

  • OEM product launch or SoC bring-up experience.

Soft Skills:

  • Excellent communication and cross-functional collaboration.

  • Leadership in technical decision-making.

  • Ability to translate complex hardware/software constraints into practical solutions.

  • Mentorship and technical coaching for junior engineers.

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