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Audio Engineer V

Spectraforce Technologies
United States, Washington, Redmond
Sep 30, 2026
Job Title: Audio Engineer V

Location: Redmond, WA

Duration: 12 months (Possible Extension)

Job Description:

Role Summary:

  • We are looking for a contingent Audio Render Tuning Engineer to support Client's research AR glasses audio program.
  • This role focuses on render-path DSP tuning of the speaker system using Client's internally developed embedded audio processing framework and tuning tools.
  • The successful candidate will be hands-on in the lab, working closely with the Research Audio team to deliver a tuned, shipping-quality speaker experience.



What makes this role interesting?

  • This is an opportunity to own the audio tuning of a next-generation Client research AR glasses device end to end.
  • The contractor will work inside Client's Reality Labs Research organization on Aria 2+, a data-collection glasses platform used by researchers, and will have a direct, visible impact on how the device sounds.
  • The role offers a rare combination of deep hands-on lab work - anechoic chamber measurement, electroacoustic characterization, subjective listening evaluation - with exposure to Client's internally developed embedded audio DSP framework and tuning toolchain, supported by the internal tooling teams that build it.
  • The contractor will collaborate closely with hardware, firmware, algorithms, mechanical, optics, and vendor partners, giving broad visibility across a full product development cycle from early samples through multiple hardware build stages. Because the work is research-driven prototyping with the intent of feeding future products, the contractor gets to shape technology at the earliest stage.



Must-Have Skills:

  1. Hands-on DSP tuning on a speaker-type device. This is the single most important requirement. Knowing about these algorithms or having tested them is not sufficient - the candidate must have personally performed the tuning.
  2. Audio DSP fundamentals. Must understand what equalization, dynamic range compression, limiting, and speaker protection do, how they function, how they are used, and what the trade-offs are.
  3. Ability to apply and tune existing algorithms on an audio system (an audio systems engineer profile). Writing algorithms from scratch is not required.



Nice-to-have Skills

  1. Direct AR/VR glasses or other head-worn audio device experience.
  2. Transducer-level characterization and speaker integration experience (T/S parameters, Klippel, impedance, excursion).
  3. Exposure to embedded audio middleware or firmware-level audio bring-up (Audio Weaver, Qualcomm QACT, ADSP integration).



Years of overall experience required?

  • 10+ years



Degrees/certifications required?

  • Bachelor's degree in Electrical Engineering, Mechanical Engineering, Acoustics Engineering, or a related technical discipline



Key Responsibilities:

  • Render DSP Tuning: Perform speaker render-path tuning for research AR glasses using the company's internally-developed embedded audio DSP framework and associated MATLAB-based tuning tools
  • Tuning Components: Design and apply equalization filters, tune dynamic range compression and limiter parameters to optimize loudness, dynamics, sound quality, and distortion across use cases (media, voice, speech) while preserving speaker integrity
  • Speaker Characterization & Baseline Measurement: Measure devices to establish baseline performance, collect frequency response, distortion (THD), and impedance data in anechoic or controlled acoustic environments
  • Tuning Profile Management: Generate, compile, and validate tuning profiles via Client's internal tuning toolchain for deployment to device firmware
  • Collaboration with Cross-Functional Teams: Work with hardware, firmware, algorithms, and research teams to align tuning with system-level requirements
  • Maintain tuning documentation, test reports, and configuration records for each tuning iteration and release candidate
  • Tool Onboarding: Ramp up on Client's internal audio DSP ecosystem including graphical pipeline editors, render tuning tools, and device control utilities with support from internal tooling teams



Required Qualifications:

  • Prior experience performing audio systems render tuning for consumer electronics products (AR/VR glasses, hearables, headphones, wearables, telecom devices, smart speakers)
  • Understanding of render DSP tuning approaches (EQ, DRC, limiting, speaker protection) and hands-on experience performing tuning in a lab environment
  • Experience with electroacoustic measurement tools (e.g. Audio Precision (APx series), Listen SoundCheck, HEAD acoustics ACQUA) and measurement transducers
  • Experience with MATLAB for audio signal processing, filter design, and tuning tool workflows
  • Strong attention to detail and systematic approach to parameter optimization and documentation
  • Ability to work independently on tuning tasks while collaborating with a broader audio engineering team
  • Understanding of speaker protection algorithms (excursion limiting, thermal protection, brownout protection)
  • Bachelor's degree in electrical engineering, Mechanical Engineering, Acoustics Engineering, or a related technical discipline



Preferred Qualifications:

  • Experience with speaker integration and transducer-level characterization (T/S parameters, Klippel, impedance, excursion)
  • Exposure to DSP frameworks or audio middleware (AudioWeaver, Qualcomm QACT, or similar embedded audio toolchains)
  • Experience with volume table tuning and perceptual loudness optimization
  • Exposure to firmware-level audio bring-up or ADSP integration workflows
  • Experience with capture-path audio tuning including any of beamforming and spatial filtering, noise suppression, wind noise rejection, wake-word/keyword detection and speech recognition testing, capture-path gain staging and mic array calibration



Interview Process:

  • How many rounds of interviews? 2 - 3 rounds



Types of Interviews:

  • Round 1: initial screen with CWAM - general and behavioral questions to understand the candidate.
  • Round 2: technical panel, in-depth on signal processing and cross-functional collaboration.


Interview Duration: 45 minutes to 1 hour per round

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