Magma Software Engineer – Acoustic Sensing JB-5556

Acoustic Signal Processing Senior Engineer – Underwater Sensing.

We are a well-funded startup focused on undersea applications — sensing and autonomous underwater vehicles (AUVs).

Following a successful early funding round, we are building next-generation underwater acoustic sensing systems that combine optical fibers, advanced interferometry, and signal processing to redefine how the world perceives the undersea domain.

We are a small, focused team working from the ground up on a proven IP-protected concept, tackling complex and fascinating technological challenges across optics, acoustics, mechanics, materials, and software.

We are looking for an Acoustic Signal Processing Engineer to own the back end of our sensing system — from raw demodulated optical signals all the way to high-level acoustic applications.

You will also deeply understand and lead the optical front-end relevant to your domain: the coherent interrogation system, phase demodulation, and the optical noise floor that ultimately limits what you can detect.

This role sits at the intersection of physics, signal processing, and applied algorithms.

You will develop methods to extract weak acoustic signals from noisy distributed fiber data, improve SNR, and build detection and analysis applications that turn raw measurements into actionable intelligence.

What You'll Do:

Signal Processing:

• Develop and implement acoustic signal extraction algorithms from distributed fiber phase data

• Characterize and improve system SNR: spatial filtering, temporal filtering, noise modeling, and signal processing techniques

• Develop demodulation and phase-unwrapping algorithms robust to real-world optical noise

• Design and run controlled acoustic pool and field experiments; define signal processing validation protocols.

Optical Front-End (Signal Perspective):

• Understand and characterize the coherent interrogator: laser phase noise, interferometric demodulation, and fundamental noise sources

• Define optical system requirements from a signal processing perspective — noise floor, dynamic range, sampling rate, bandwidth

• Work hands-on with the optical bench to validate demodulation quality and diagnose signal artifacts

Higher-Level Applications:

• Develop detection, localization, and classification algorithms for acoustic events and targets

• Explore machine learning and statistical methods to extract features from large acoustic datasets.

• Define performance metrics and validate algorithms against ground truth data from field experiments.

• Document findings, algorithms, and results systematically; lead technical reviews in your domain.

Collaboration:

• Work closely with the sensor interface and company technical leaders to align optical and signal processing design decisions

• Participate in field deployments as the signal processing lead — configure acquisition, monitor data quality, and perform post-analysis.

Requirements:

Must Have:

• MSc in Electrical Engineering, Acoustics, Physics, Applied Math, or a related field (PhD in signal processing or acoustics – an advantage)

• At least 7 years of experience in acoustic signal processing

• Proven experience with underwater sensing technologies and applications

• Strong command of digital signal processing – filtering, spectral analysis, statistical estimation and array processing – and its application in underwater environments

• Hands-on algorithm development in Python (NumPy, SciPy) and/or MATLAB

• Experience with data acquisition systems and real-time or near-real-time signal analysis, including sensor integration and calibration

• Excellent communication skills and ability to work in a team environment.

An Advantage:

• Fiber-optic sensing systems: DAS, interferometry, phase-OTDR.

• Coherent optical detection, phase demodulation and phase unwrapping.

• Sonar signal processing or acoustic sensor systems.

• Machine learning applied to time-series or acoustic data.

• Designing and executing field and pool experiments, and processing field datasets.