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Ppg Signal Processing Jobs (NOW HIRING)

Align Technology

Staff R&D Engineer-Algorithm

San Jose, CA · On-site

$210K - $288K/yr

... signal processing, machine learning, and physiological data analysis (e.g., PPG, ECG, accelerometry). * ​Strong experience working with wearable sensors and evaluating sensor signal quality and ...

Align Technology

Staff R&D Engineer-Algorithm

San Jose, CA · On-site

$210K - $288K/yr

Deep expertise in signal processing, machine learning, and physiological data analysis (e.g., PPG, ECG, accelerometry). * Strong experience working with wearable sensors and evaluating sensor signal ...

NCIRE

Staff Research Associate II

San Francisco, CA · On-site +1

Acquire, process, and organize multi-modal psychophysiological signals , including electrodermal ... PPG) signals derived from video . * Conduct and score clinical interviews and self-report measures ...

NCIRE

Staff Research Associate II

San Francisco, CA · On-site +1

Acquire, process, and organize multi-modal psychophysiological signals , including electrodermal ... PPG) signals derived from video . * Conduct and score clinical interviews and self-report measures ...

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Ppg Signal Processing information

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$53.5K

$131.3K

$193.5K

How much do ppg signal processing jobs pay per year?

As of Jun 11, 2026, the average yearly pay for ppg signal processing in the United States is $131,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $147,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in PPG signal processing and how can they be addressed?

Professionals in PPG (photoplethysmography) signal processing often face challenges such as motion artifacts, ambient light interference, and variability in physiological signals among individuals. Addressing these issues typically involves implementing advanced filtering techniques, adaptive algorithms, and robust validation protocols to ensure accurate data extraction. Collaboration with hardware engineers and clinical experts is also essential to optimize sensor design and data collection procedures. Staying updated with the latest signal processing methodologies and participating in interdisciplinary teams can help overcome these challenges and ensure high-quality outcomes.

What is the future of signal processing?

The future of signal processing, including PPG signal processing, involves advancements in machine learning and real-time analysis to improve accuracy and efficiency. Growing use of wearable devices and IoT applications will increase demand for skilled professionals who can develop algorithms and optimize hardware for diverse environments.

What is PPG signal processing?

PPG signal processing refers to the techniques used to analyze and interpret photoplethysmography (PPG) signals, which are non-invasive measurements of blood volume changes in the microvascular bed of tissue. These signals are typically collected using optical sensors placed on the skin, such as in wearable fitness trackers or medical devices. Processing PPG signals involves filtering out noise, extracting physiological features like heart rate or oxygen saturation, and sometimes detecting anomalies. Advanced algorithms can further analyze these signals to assess cardiovascular health or other vital signs.

What are the key skills and qualifications needed to thrive as a PPG Signal Processing Specialist, and why are they important?

To thrive as a PPG Signal Processing Specialist, you need a strong background in biomedical engineering, signal processing, and programming, usually supported by a relevant degree. Familiarity with tools like MATLAB, Python, and specialized signal analysis software, as well as knowledge of wearable sensor technology, is typically required. Strong analytical thinking, attention to detail, and effective communication skills set top performers apart in this field. These competencies are essential to accurately interpret physiological data from photoplethysmography (PPG) signals, enabling the development of reliable health monitoring solutions.

Does signal processing pay well?

Signal processing jobs, including roles like PPG signal processing, tend to offer competitive salaries, especially for those with specialized skills in algorithms, programming, and data analysis. Salaries vary based on experience, education, and industry, but professionals in this field often earn above average wages compared to many other engineering roles.

What is the difference between Ppg Signal Processing vs Ppg Signal Processing?

AspectPpg Signal Processing

Since the comparison is between the same job title, there is no difference in roles, skills, or industry usage. Both involve analyzing photoplethysmogram signals to extract vital health information, requiring knowledge of signal processing, biomedical engineering, and data analysis. Professionals typically work in healthcare, medical device companies, or research institutions. The focus remains on developing algorithms, filtering signals, and interpreting data to support medical diagnostics.

Is ML a high paying job?

Machine learning (ML) roles, including those related to PPG signal processing, are generally well-compensated due to high demand for specialized skills in data analysis, programming, and algorithms. Salaries vary based on experience, location, and industry, but advanced ML positions often offer above-average pay compared to many other tech roles.

Is signal processing a good career?

Signal processing is a specialized field within engineering and data analysis that involves analyzing and interpreting signals such as audio, video, or biomedical data. Careers in this area often require knowledge of algorithms, programming, and tools like MATLAB or Python, and can lead to roles in industries such as telecommunications, healthcare, and defense. It offers opportunities for innovation, research, and development with steady demand for skilled professionals.
Infographic showing various Ppg Signal Processing job openings in the United States as of June 2026, with employment types broken down into 95% Full Time, 1% Part Time, 1% Temporary, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $131,349 per year, or $63.1 per hour.
Signal Processing Engineer

Signal Processing Engineer

Norbert Health

New York, NY • On-site

Full-time

Posted 4 days ago

Job description

The company

Norbert is building autonomous robots that deliver healthcare.

Our AI sensing platform mounts on mobile robots and does the work of a care team memberrounding on patients, capturing vitals without contact (FDA-cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously.

We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030.

We're a small, international team backed by top-tier VCs, with offices in Brooklyn and Paris. We ship things that matter.

The position

We're looking for a Signal Processing Engineer to join our algorithm and development team, working on remote vital sign monitoring from video. You'll develop and validate algorithms that extract clinical-grade physiological signals (heart rate, blood pressure, respiration) from camera data, working closely with computer vision engineers in our algorithm team.

What You'll Do:

  • Design and implement signal processing algorithms for extracting vital signs from video-based sensors (rPPG, rBP)
  • Develop real-time filtering, denoising, and feature extraction methods to achieve clinical-grade accuracy
  • Build validation pipelines comparing our video-based measurements against clinical reference devices (ECG, PPG, BP monitors)
  • Help design studies that ensure millisecond-level synchronization between video streams and reference sensors for accurate ground truth
  • Integrate with the computer vision pipeline (C++) to leverage multi-modal signal enhancement techniques
  • Architect cloud-based QA and automated verification systems for reproducible algorithm validation
  • Prototype algorithms in Python and C++ before deploying them on our production system

What We're Looking For:

  • Master's degree in Electrical Engineering, Biomedical Engineering, or related field (or PhD)
  • Strong fundamentals in digital signal processing, statistical methods, and real-time systems
  • Deep expertise in physiological signal processing (PPG, ECG, respiration, blood pressure)
  • Experience processing low-frequency physiological signals with challenging SNR characteristics
  • Proficiency in both Python (prototyping) and C++ (production integration)
  • Experience with spectral analysis, adaptive filtering, and time-domain methods for real-time applications
  • Ability to work independently, solve complex problems, and drive projects to completion
  • 5+ years industry experience developing signal processing algorithms for medical or physiological sensing applications (or equivalent with PhD)

Bonus Points:

  • Experience with contact-based and contactless vital sign measurement technologies
  • Background working with medical-grade measurement devices and clinical reference standards
  • Experience with embedded signal processing (ARM, edge devices)
  • Knowledge of motion artifact removal and noise reduction in challenging environments
  • Familiarity with DevOps practices for reproducible research (experiment tracking, data versioning)
  • Background in medical devices, regulated environments, or clinical validation studie

What We Offer:

  • Real impact: your code provides care for patients today
  • High autonomy and technical ownership - you'll define our signal processing approach
  • Work at the intersection of cutting-edge AI, edge computing, and healthcare
  • A talented, excellent, diverse and international team
  • Talented, international team tackling meaningful problems in healthcare
  • Equity participation in the company's future
  • Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
  • Transparent, mission-driven culture focused on continuous learning
  • Competitive salary and equity