🧠 [Hiring] Applied ML Engineer (IoT / Anomaly Detection) – Remote, Western Time Zones | LUNAVII
Source: reddit-r-remotejs
Hey everyone 👋
I’m Elvis, CTO at LUNAVII — we’re building the smallest and smartest child safety bracelet powered by AI. Our mission is simple but ambitious: use intelligent anomaly detection to prevent emergencies before they happen.
We’re now looking for an Applied Machine Learning Engineer who’s excited about bringing ML to life on real devices — detecting things like forced removal, fever, or unusual motion patterns from multi-sensor data.
About the Role
You’ll design and deploy an anomaly detection system that learns a child’s normal behavior and flags emergencies in real time.
Think:
- Detecting forced vs normal removal using temperature and motion data
- Recognizing runaway or panic motion
- Differentiating water immersion vs hand washing
- Learning routine patterns to minimize false alarms
It’s not just modeling — it’s applied intelligence for a real-world product that could save lives.
What You'll Work With
Tech stack / tools:
- Python (pandas, scikit-learn, PyTorch or TensorFlow)
- AWS Lambda, S3, DynamoDB, CloudWatch, SNS
- IoT / time-series / anomaly detection
- Bonus: experience with sensor data simulation or edge ML
Requirements
- Strong experience in ML applied to real-world data (time series, sensors, IoT, or wearables)
- Ability to design detection logic, not just train models
- Experience deploying ML pipelines on AWS
- Comfortable writing clear, production-ready code
- Independent, practical, and startup-minded
Details
- 🌐 Remote-first (preferably in Western time zones)
- 💰 Flexible contract or part-time role, potential to convert to full-time
- 📈 Opportunity for equity as we scale
- 🧩 Work directly with the founding team shaping our AI safety core
How to Apply
If this sounds like your kind of challenge, DM me here on Reddit or send a quick email to 📬 elvis@theworldoflunavii.com
Include your GitHub, Kaggle, or project links — we care more about what you’ve built than where you’ve worked.
Let’s make wearable AI truly intelligent. 🧠