
Senior QA Engineer, AI Wearables and Machine Learning
NextSense, Inc • Mountain View, California, United States
Salary: $100,000 - $150,000 / year
**Role & seniority: ** First dedicated QA hire; hands-on, full ownership of quality; reports to VP Engineering; QA lifecycle ownership with path to leading QA function.
**Location & work type: ** Mountain View, CA (hybrid); work-from-home flexibility. US work authorization required.
**Stack/tools: **
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Mobile iOS: XCTest / XCUITest (or similar)
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Backend/API testing: API test frameworks
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CI/CD: CI integration, release quality gates
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Hardware-in-the-loop: automated tests on real earbuds
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ML/on-device validation: regression across model versions; Core ML/on-device inference (mentioned)
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Cloud/data/analytics (nice-to-have): GCP, Firebase, BigQuery, Mixpanel
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Wireless (nice-to-have): Bluetooth/BLE, audio streaming
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Release management (nice-to-have): TestFlight, phased rollouts
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AI-first workflow (preferred): AI tools for test generation/triage/automation authoring
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Top 3 responsibilities:
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Design & execute test plans across iOS app, embedded earbud firmware, ML pipelines (on-device + cloud), and backend—including sleep/meditation/focus sessions, EEG signal quality, BT connectivity, battery life.
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Build QA automation & infrastructure from scratch: mobile UI automation, API tests, hardware-in-the-loop, CI integration, release quality gates.
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Validate ML- and analytics-driven features: regression across model versions, ground-
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Full Description
About Nextsense
At NextSense (https: //nextsense.io/), our mission is to restore energy, joy, and purpose to daily life through clinically validated brain-sensing technology. Based in Mountain View, CA, our multi-modal smart earbud platform is designed to enhance sleep at night, deepen meditation, and sharpen focus throughout the day. Join us in shaping the future of wearable EEG and machine-learning-driven insights.
Your Role
You will be our first dedicated QA hire: hands-on from day one, with full ownership of quality across the product. We are a close-knit team of experts in hardware, software, algorithms, and neuroscience.
Own quality across our entire product suite: the iOS app, embedded earbud EEG firmware, on-device and cloud machine-learning pipelines, and our cloud backend.
Design and execute rigorous test plans for things most QA teams never touch: overnight sleep sessions, meditation, focus, EEG signal quality, Bluetooth connectivity and battery life.
Build test automation and infrastructure from the ground up: mobile UI automation, API tests, hardware-in-the-loop testing (automated tests running against real earbuds), CI integration, and release quality gates for both app and firmware. Validate machine-learning-driven features (sleep staging, meditation and focus detection): regression across model versions, ground-truth datasets, and signal-quality edge cases.
Verify analytics instrumentation: our product and business decisions run on event data, so its correctness is a quality surface you own.
AI-first: our engineering org uses AI tools for development, test generation, triage, and automation authoring. Collaborate with engineers, UX designers, scientists, and teammates across US and Asia time zones to uphold quality standards in a startup environment. Reporting to the VP of Engineering, you will oversee the full QA lifecycle, from test strategy and planning to execution. As we grow, there is a clear path to leading the QA function.
Essentials
Experience: 3-5 years in QA with hands-on depth in mobile (iOS) plus at least one of: embedded firmware/hardware, machine-learning systems, or cloud backends.
Technical Skills: Experience with iOS test frameworks (XCTest/XCUITest or similar), API testing, and CI/CD pipelines.
AI Fluency: You use AI tools in your daily work (test design, automation authoring, log triage) and are eager to push what modern QA can be.
Collaboration: Excellent communication skills and experience working with cross-functional, distributed teams.
Attention to Detail: Highly organized, data-driven, able to create actionable reports and drive quality to resolution.
Startup Mindset: Adapt and thrive in a fast-paced, dynamic environment; comfortable wearing multiple hats. At this time, we're only able to consider applicants who are legally authorized to work in the United States.
Desired: Familiarity with any of the following Wireless connectivity testing (Bluetooth/BLE, audio streaming)
Machine Learning: fundamentals and testing ML models (e.g., Core ML, on-device inference; evaluating models with metrics like sensitivity/specificity)
Hardware Testing: validating devices that use biosignals (e.g., EEG or other wearables)
Cloud and Data: GCP, Firebase, BigQuery; analytics platforms such as Mixpanel Mobile release management (TestFlight, phased rollouts)
Company culture and values At NextSense, we value hard work but also believe in enjoying the journey. Our fast-paced environment is balanced with a fun, collaborative atmosphere that fosters innovation and creativity. We are hands-on, often wearing multiple hats to drive our mission forward. There is ample room for professional growth, with opportunities to learn, take on new challenges, and make a significant impact.
Our culture proceeds from our core values: Conviction, Connection, Curiosity, Compassion, Candor, and Co-Founder Mentality.
Benefits and Perks
Competitive Salary: $100K-$150K plus stock options
Comprehensive Health Insurance: Medical, dental, and vision
Hybrid Work: Based in our Mountain View, CA office, with work-from-home flexibility
Collaborative Work Environment: Supportive, cross-functional teams with opportunities to travel for sync-ups
Make a Real Impact: Work on a mission-driven product that restores joy, energy, and purpose
Application Process
Our application process is designed to ensure the best fit for both you and NextSense. It includes
Application: Submit your resume and a brief paragraph explaining why our mission resonates with you.
Screening Interview: A short call to align on goals and experience.
Team Interviews: 2-4 sessions with various team members to explore technical skills, collaboration style, and cultural fit.