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Job Summary We are seeking an Embedded Audio & ML Application Validation Engineer to validate MCU-based audio, voice, and machine learning applications on target hardware. The engineer will measure and report audio and voice activation KPIs, execute acoustic lab measurements, analyze power behavior, compare firmware-level performance, and document defects and validation outcomes. Key Responsibilities - Validate MCU-based audio, voice, and machine learning applications on target hardware against test plans and release criteria. - Measure and report power, wake-word or voice trigger behavior, latency, reliability, and related voice activation KPIs. - Perform acoustic lab measurements under defined quiet, noisy, near-field, and far-field conditions. - Execute repeatable test procedures, maintain measurement data, and compare KPIs across firmware versions and configurations. - Support power analysis for always-on and low-power voice activation modes. - Identify and flag firmware regressions or major performance changes. - Perform basic debugging using logs, traces, lab observations, and measurement equipment. - Document results, KPI trends, issues, observations, and recommended next steps. Required Technical Skills Mandatory - 4-6 years in embedded validation, application testing, firmware testing, or performance measurement on MCU platforms. - Working knowledge of Python or similar scripting for automation, log parsing, KPI collection, and reporting. - Good C programming knowledge and basic embedded debugging skills. - Basic understanding of MCU architecture, low-power modes, peripherals, and real-time behavior. - Basic hardware knowledge and ability to use lab instruments for board checks and power measurements. - Valuable documentation skills for results, trends, issues, and recommended actions. Preferred Skills - Exposure to audio or voice use cases such as wake-word, VAD, AEC, noise suppression, or audio front-end validation. - Familiarity with PDM microphones, I2S/TDM, I2C, SPI, UART, DMA, and common MCU interfaces. - Experience in acoustic lab measurements for voice or audio performance. - Understanding of trade-offs between accuracy, latency, CPU load, memory usage, and power. Educational Qualification - B.Tech / M.Tech in Electronics, Electrical Engineering, Computer Science, Embedded Systems, or a related field. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.