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AI Wearable Health Anomaly Detection Developer

Paisley Suzuki

Full-time · Job · Los_Angeles

About the role

Smartwatches collect heart rate, SpO2, activity, and sleep data continuously — but most of that data sits unused until someone has a health scare and asks their doctor to look at it retroactively. Our anomaly detection system monitors wearable data streams in real time, identifying patterns that warrant medical attention: irregular heart rhythms, sudden fitness declines, sleep pattern disruptions, and activity changes that correlate with clinical deterioration. As a junior developer, you'll build the data processing pipelines that transform raw wearable sensor streams into clean, feature-rich time series suitable for anomaly detection. That means handling missing data from sensor dropouts, normalizing readings across different device models, computing rolling physiological baselines, and flagging readings that deviate significantly from each user's personal normal. The digital health team is five engineers. You'll start with the data preprocessing layer, learning how wearable sensor data behaves in the real world — noisy, incomplete, and full of artifacts from wrist movement, water exposure, and improper wear. By month three, you'll own the baseline computation module.

Responsibilities

  • Build data processing pipelines for wearable sensor streams
  • Handle missing data, sensor dropouts, and device-specific normalization
  • Compute rolling physiological baselines per user
  • Flag readings deviating significantly from personal baselines
  • Write tests for preprocessing accuracy across device types
  • Document data quality patterns and artifact handling rules

Requirements

  • 1+ year of Python development with data processing experience
  • Basic understanding of time series data and statistics
  • Familiarity with pandas for data manipulation
  • Interest in digital health and wearable technology
  • Attention to detail for health-critical data processing

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $1,500 learning stipend
  • Mentorship from senior health data engineers
  • Work that helps people live healthier lives

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Categories

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python pytorch docker aws pandas

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python pytorch docker aws pandas statistics

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