Spatial Audio Engineer

Sonovagroup — Germany · Posted ~18 hours ago

Skills

spatial audio audio signal processing deep learning data engineering multichannel rendering room acoustics DNN training DNN

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Summary ✨ AI‑Generated

A Spatial Audio Engineer role focused on developing high-fidelity acoustic simulations and spatial audio pipelines for deep-learning systems. You will combine signal processing, multichannel rendering, data engineering, and machine learning to create realistic training environments and improve audio algorithms for assistive technology.

Highlights

Develop high-fidelity spatial audio pipelines for deep-learning training and evaluation, build realistic acoustic simulations, analyze model behavior, and contribute directly to advanced hearing-aid algorithms.

Description

More About The Role We are looking for a Spatial Audio Engineer to help develop our next-generation, DNN-based hearing-aid algorithms. In this role, you will create realistic spatial simulations to understand and shape how our models behave in challenging everyday acoustic scenes, with direct impact on hearing-aid users. Your responsibilities will include: Building and improving high-fidelity spatial audio pipelines for DNN training and evaluation, covering simulated room acoustics, multichannel rendering, spatial audio, audio signal processing, data engineering, and deep learning.Creating tools and analyses to validate realistic spatial audio scenes and understand how spatial training data affects model behavior in complex everyday acoustic environments,Working closely with Audatic’s deep learning engineers to keep training data diverse, physically plausible, perceptually meaningful, and aligned with our DNN models.Contributing to hearing-aid algorithms that use subtle spatial cues from multiple microphones to separate speech from noise, preserve acoustic-scene awareness, and improve communication in demanding real-world environments. More About You A bachelor’s or master’s degree in a technical field and at least 5 years of relevant experience or a Ph.D. in the field of audio processing and at least 2 years of relevant experience.Expertise in spatial audio, such as ambisonics, HRTFs, room simulation, binaural rendering, or other spatialization techniques.Practical knowledge of room-acoustic measures such as RT60, DRR, early reflections, late reverberation, clarity, and diffuseness, and how to use them to validate simulated environments.Strong foundations in audio digital signal processing (DSP).Experience in spatial perception, including cues and concepts such as ITD, ILD, interaural coherence, localization, externalization, or related perceptual metrics.Strong Python proficiency and a demonstrated ability to write robust, clean, maintainable code.Familiarity with deep learning concepts, including training data, targets, loss functions, model evaluation, and how data quality affects model behavior.Experience developing DNN training data pipelines or working directly with deep learning models is a strong plus.Dependable communication skills with full professional proficiency in English. More About What We Offer At Audatic, you’ll be part of a diverse, international, and passionate team that values collaboration and innovation. We provide an environment that allows you to balance professional growth with personal well-being. Competitive compensation package30 days of paid vacationConference visits and the opportunity to publish relevant discoveriesFree daily meals, drinks, and snacks at our green and modern office in the heart of BerlinRegular team events and a yearly retreatCompany-sponsored public transport ticket (Deutschlandticket)Hybrid work model (at least 60% on-site) Sonova is an equal opportunity employer. We team up. We grow talent. We collaborate with people of diverse backgrounds to win with the best team in the market place. We guarantee every person equal treatment in regard to employment and opportunity for employment, regardless of a candidate’s ethnic or national origin, religion, sexual orientation or marital status, gender, genetic identity, age, disability or any other legally protected status.