Biomedical Processing Engineer

LifeLens Technologies Inc.•Ivyland, PA

2d•Onsite

About The Position

LifeLens Technologies, Inc. is a medical device developer located in Ivyland, PA. We are pioneering innovative, next-generation treatment devices for personal health monitoring. We are seeking to hire a Biomedical Signal Processing Scientist. In this role, you will have the opportunity to work on cutting-edge technologies designed to revolutionize wearable health care. You have a collaborative mindset and a passion for developing new technology. You are detail-oriented and goal-driven. You are a capable problem solver with excellent organizational skills and superior verbal and written communication skills. Your passion and drive will be rewarded with a competitive salary, benefits, and long-term growth opportunities. This is a full-time, on-site position. Summary You will develop and validate algorithms that turn signals from the Company's multi-sensor wearable hubs, including PPG, ECG, and accelerometry, into clinical and consumer health measurements. The role spans two kinds of work: offline analysis of high-volume clinical and field recordings, and real-time algorithms that run on the device. Working alongside senior scientists and with hardware, firmware, and clinical teams, you will build and test algorithms, run analyses, and contribute to clinical validation. As the Company expands into consumer products, you will have room to grow into owning measurements from prototype through validation.

Requirements

Foundation in digital signal processing and time-series analysis.
Experience analyzing physiological or other real-world sensor signals, through research, coursework, or industry.
Proficiency in Python; MATLAB experience is helpful.
Experimental design and applied statistics.
Familiarity with machine learning methods.
Data analysis and visualization skills.
Ability to learn new domains quickly and act on feedback.
Ability to communicate technical results clearly.
PhD, Master's degree, or Bachelor's degree with 2+ years of relevant experience.
Degree in biomedical engineering, electrical engineering, neuroscience, physics, applied mathematics, computer science, or a related quantitative field.
Research experience, including graduate research, counts toward relevant experience.

Nice To Haves

Research or coursework on PPG, ECG, SpO2, remote PPG, respiration, or other bio-signals.
Background in neural or cardiac electrophysiology or optical recording (e.g., calcium imaging, fiber photometry, cardiac optical mapping).
Experience with event detection in noisy time series.
Experience with version control, testing, and reproducible analysis workflows.
Familiarity with C or embedded systems.
Exposure to medical device development or regulated environments.
Recent graduates are encouraged to apply.

Responsibilities

Developing and testing algorithms that derive physiological measurements from multiple sensors, including PPG, ECG, and accelerometry.
Conducting offline analyses of large clinical and field datasets to characterize signal behavior, failure modes, and algorithm performance.
Developing methods robust to motion artifact and other real-world conditions.
Building and maintaining data processing pipelines and analysis tools.
Supporting the adaptation of algorithms for real-time use on the device.
Contributing to the design and analysis of validation studies against clinical reference devices.
Contributing to verification and validation documentation for regulatory submissions.
Writing efficient, tested, and reproducible code.
Communicating results to technical and nontechnical audiences.
Collaborating across engineering disciplines to solve problems, improve existing products, and meet deadlines.
Other tasks as assigned.