Physiological Signal Processing Engineer (rPPG / Mobile Biosensing)

Job Title: Senior Signal Processing Engineer

Experience: 5+ years

Contract duration: 3-6 Months

Shift timings: Vietnam business hours (9:00 AM – 6:00 PM)

Job Summary

Physiological Signal Processing Engineer

core signal engineering role

Key Responsibilities

• Design, optimize, and maintain

  rPPG / TOI signal-processing pipelines

  using RGB and IR video
• Implement

  multi-stage preprocessing and denoising

  techniques to suppress motion and illumination artifacts
• Develop and apply

  signal quality scoring and confidence metrics

  for physiological signals
• Apply advanced signal-processing methods including: Adaptive filtering, CA / PCA-based approaches, Color-space transformations, Skin ROI detection and stabilization
• Build

  cross-device normalization strategies

  and error-bounded estimators
• Define

  biomarker-level acceptance criteria

  , failure modes, and signal validity thresholds
• Validate algorithms using

  ground-truth physiological references

• Collaborate with

  iOS and ML teams

  to integrate algorithms into on-device or hybrid pipelines
• Produce

  technical documentation

  suitable for regulatory review and platform approvals (including Apple review support)

Expected Deliverables

• Comprehensive benchmark reports across device models, skin tones, lighting conditions, and motion scenarios.
• Biomarker feature specification sheets, including recommended thresholds and confidence bands.
• A/B evaluation results demonstrating improvements in signal stability, missingness, and downstream inference performance.

Required Qualifications

• 5+ years of experience in

  physiological signal processing or computational biomedical engineering

• Strong hands-on experience with:
• rPPG and camera-based physiological sensing
• HR / HRV estimation and artifact mitigation
• Time-series signal analysis under real-world conditions
• Strong programming skills in

  Python

• Experience with at least one real-time or production runtime:
• C++, Swift, Metal, or equivalent
• Proven experience validating algorithms with

  ground-truth comparisons

  (not lab-only or synthetic data)

Nice to Have

• Experience with camera-based

  BP-adjacent proxies

• Exposure to

  stress or autonomic nervous system (ANS) metrics

• Experience with

  multimodal signal fusion

• Publications or commercial work in

  consumer-grade biosensing

• Experience building or supporting

  wellness-grade claims frameworks

Important Note

• This role is

  not

  a general ML or data science position
• Candidates focused primarily on model training without strong signal-processing fundamentals may not be a good fit
• Deep understanding of signal behavior, noise sources, and algorithmic trade-offs is essential