Get your free practice interview for this role
micro1 screens applicants online, often with an AI interview. micro1 offers a free, 18-minute AI practice interview with feedback, and we picked the one closest to this role: Manufacturing Engineer. It covers:
Here’s your practice interview
Allow your microphone when it asks, find a quiet spot, and give yourself about 20 minutes. We’ve also emailed you the link and the free ebook.
Step 2: when you feel ready, apply.
The practice interview is free and run by micro1. Land Remote Jobs is an independent job board, not part of micro1, Mercor or Turing. Practising helps you prepare; it can’t guarantee the result of your real interview. Want more tips? Read our free micro1 interview guide.
Apply for this role
You apply on micro1's own site. It’s free, and you can apply even if you skip the practice.
Who this role suits
Engineers and technical specialists who want remote project work that uses their design and manufacturing experience.
Full job description
Role Title: PhysioNet Competitor (Biomedical Signal Processing & ML)
Pay: $60–$120/hour
Location: Global, fully remote
Job Type: Contractor (~15 hours per week)
Schedule: Flexible-you choose the hours and days you work, including weekends if desired
micro1 is engaging specialists with experience in the PhysioNet Challenge or comparable biomedical signal processing and machine learning competitions. In this role, you will apply your scientific programming, signal processing, and modeling expertise to create, solve, and evaluate advanced technical problems that help improve next-generation AI systems.
We are looking for people who have worked directly with physiological signals and can turn noisy, real-world data into a rigorous and reproducible analysis. Strong candidates will be able to explain the methods they developed, the experiments they ran, the technical decisions they personally owned, and how they validated their results. No prior experience working on AI training projects is required.
Scope of Work
- Create technically rigorous, self-contained problems involving biomedical signals, time-series data, signal processing, and machine learning.
- Develop clear reference solutions using Python, MATLAB, or another appropriate scientific computing environment.
- Work with tasks involving signal preprocessing, filtering, segmentation, feature extraction, representation learning, classification, or forecasting.
Preferred Qualifications
- Participation in a PhysioNet/Computing in Cardiology Challenge or a comparable biomedical signal processing or scientific machine learning competition.
- Strong competition results and evidence of a substantive personal technical contribution.
- Public evidence of your work through an official team result, conference paper, technical report, open-source repository, or meaningful code contribution.
- Hands-on experience with physiological signals such as ECG, EEG, PPG, EMG, respiratory signals, polysomnography, or other clinical time-series data.
Process
- Apply to the role and complete the screening questions.
- Complete an AI interview of approximately 30 minutes.
- Complete the hiring manager review.
Compensation Structure
Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.
Minimum submission requirements apply.
Start Timeline & Availability
- We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.
Last checked open on Oct 28, 2026. Job description provided by micro1.
Something not working? Tell us
If the practice interview or the apply link doesn’t open, or the job looks closed, let us know and we’ll fix it.
Thanks, we got it. We’ll check this job’s links and reply by email if you left one.