Wualt is building a smart ring for women's safety and everyday wellness. The ring senses what the body is doing and, when it matters, alerts the people a wearer trusts. We are a funded, pre-launch hardware startup heading into our first field pilots in early 2027. Small team, real hardware, real users, close to the founders.

THE ROLE

Our ML is what turns a raw sensor stream into a signal someone can rely on. We are looking for one person to own that end to end: the models, the rigor, and a small team, and to carry them from research into a pilot-ready state. You would be the person the founders hand the ML function to.

EXPERIENCE WE EXPECT (please read before applying)

- 2 to 6 years working directly on physiological or sensor time-series ML. Your hands-on experience must include real biosignals: PPG, ECG, HRV, or accelerometer/IMU data. Depth here matters far more than total years.
- Solid signal-processing fundamentals: filtering, motion-artifact handling, feature extraction, and knowing why a model fails on real-world noise.
- Time-series deep learning (CNNs, Transformers, sequence models) and fluent, production-capable Python (NumPy, PyTorch or similar).
- You have taken at least one model to a deployed or shipped state on messy, real-world data, not just a clean benchmark.
- You understand honest evaluation: subject-wise splits (LOSO), leakage, calibration, and why a headline F1 can be a lie.
- This is not a fit for pure LLM or GenAI,



pure computer-vision, or general data-science backgrounds with no biosignal work. We screen for the signal experience specifically.

WHAT WE EXPECT YOU TO DO
- Own the ML roadmap and be accountable for pilot ML readiness. Our first field pilots start early 2027; getting the models ready, on real people and on the real device, is your deliverable.
- Build and validate the physiological models: heart rate and HRV, stress and distress detection, menstrual-cycle phase, and signal quality.
- Own the on-device and cloud ML path and work shoulder to shoulder with firmware (edge inference on the ring) and the app and cloud teams.
- Set and hold the bar for rigor: ground-truth datasets, leakage-free evaluation, and no claim about what the product can do that you cannot defend with data.
- Lead and mentor the ML and science team, and raise the whole function's standard, not just your own output.

BONUS

- Wearables, health-tech or femtech experience.
- On-device or embedded ML (we run on an nRF-class MCU, so edge inference matters).
- A patent, a publication, or a personal project that shows you can't stop thinking about biosignals.

WHAT YOU GET

- Full ownership of the ML function at a company that is weeks, not years, from putting its product on real people.
- Hardware you can hold, a pilot on a real timeline, and a direct line to the founders.
- Market-competitive salary.

📌 Lead ML Engineer, Wearable Biosignals (Chennai)
🏢 Wualt
📍 Chennai