Audio R&D Scientist – Machine Learning & DSP

Montreal     ·     Full time

About EERS

Founded in 2014, EERS Global invents, designs and tests in-ear advanced technologies to accelerate go-to-market of game-changing products. Our cutting-edge technology augments the human experience in communication in challenging situations, hearing protection, biometric and wellness monitoring, brain computer interfacing, and is repeatedly validated in the field and some have become an ANSI Standard.

Through co-development partnership, we bring a stream of new products to market. Beyond prototyping, we produce actual scalable, easily transferable, manufacturable product taking the development execution risk out of the equation.

A global centre of excellence in research in acoustics, audio and biosignal processing, in-ear technologies and product development, we attract high-caliber scientists and engineers to our team. Our head office is located in the heart of downtown Montreal. We offer competitive salaries as well as a great team environment. EERS Global is an equal-opportunity employer committed to diversity.

Job Description

Reporting to the Principal Audio R&D Scientist, the Audio R&D Scientist is responsible for developing machine learning and audio signal processing algorithms for in-ear technologies.

The position involves addressing specific challenges related to audio signal processing and optimization/machine learning that require in-depth experimentation and understanding. It involves surveying the literature, setting up test environments in MATLAB, participate in data collection, carrying out analysis of audio data, and developing algorithms on MATLAB and Python. The candidate will have to keep practical implementation in mind and, depending on skillset, will be tasked with implementing and testing the results of her/his work on an embedded platform.

The ideal candidate has strong signal processing knowledge and experience with optimization / machine learning and is interested in participating in many aspects of bringing ideas to the real world.

Duties and Responsibilities

• Participate in the design and evaluation of machine learning and signal processing algorithms.
• Characterize audio signals using FFT, spectrograms, transient separation, formant analysis, envelope extraction, etc.
• Implement feature extraction and audio processing algorithms based on DSP/ML in MATLAB/Python/JUCE, considering real-time and embedded systems implementation requirements.
• Summarize, document, and communicate findings, solutions, and strategies.
• Participate in acoustical measurements, data collection, develop experiment protocols, organize user studies.

Education and work experience

• Electrical engineering, computer science, audio/music technology or related
• Master’s degree with thesis/projects in audio
• Bachelor’s degree with relevant internship and projects in experience in audio research

Minimum Knowledge, Skills & Abilities:

• Knowledge of statistical analysis, modelling, acoustics, audio signal processing
• DSP knowledge in time-frequency analysis, denoising, dynamic equalizers, limiters / maximizers, compressors, active noise cancellation, feedback control, echo cancellation, etc.
• Experience with implementation of real-time audio applications and plugins.
• Experience with design and optimization of FIR/IIR filters.
• Strong knowledge of MATLAB, Python, C++, JUCE
• Knowledge of using DAWs such as Audacity and Reaper.
• Experience with sound and recording equipment such as microphones, audio interfaces, and loudspeakers.
• Experience with real-time operability and complexity reduction of DSP/ML algorithms targeted for embedded platforms.

Nice-to have:

• Experience in developing real-time audio applications with GUI controls on MATLAB, MaxMSP, JUCE or other C++ audio frameworks.
• Knowledge of machine learning for audio applications.
• Experience with real-time operability, complexity reduction and implementation of DSP/ML algorithms targeted for embedded platforms.

Additional skills:

• Effective written and verbal skills in English / French
• Good people and communication skills: ability to accept directions, provide and receive constructive feedback
• Strong technical aptitude: exhibit a structured and detail-oriented approach
• Excellent analytical and problem solving skills
• Strong time management and organizational skills; ability to handle multiple tasks, be punctual, and respect deadlines
• Ability to work both autonomously and collaboratively as part of multi-disciplinary teams
• Self-motivated and focused

Tagged as: AI, BCI, Machine Learning