Deep Learning Engineer

About L-Acoustics 

L-Acoustics aims to connect humans through the best shared sound experiences. We are the industry leaders in the design, manufacturing, and distribution of premium sound reinforcement technologies. Our mission is to shape the future of sound with technologies that enable audio professionals and artists to elevate the listener experience. 

Role description 

As a Deep Learning Engineer at L-Acoustics, you will play a crucial role in developing state-of-the-art deep learning models for a variety of audio projects such as source separation, metadata extraction or anomaly detection. 

At L-Acoustics, we are committed to product-driven research to ensure our deep learning models are not only innovative but also practical and ready for production. Our products primarily serve the live music industry, where high-fidelity audio and low-latency performance are essential. You will collaborate with cross-functional teams to integrate these cutting-edge solutions into our products, driving the future of live audio experiences. 

Responsibilities 

Develop state-of-the-art deep learning models for audio projects, including audio source separation, signal enhancement, and room acoustics. 

Develop datasets and conduct data preprocessing and augmentation specific to audio datasets. 

Perform model evaluation, validation, and testing to ensure robustness and accuracy. This includes building realistic test sets to minimize potential domain shifts. 

Conduct product-driven research to align deep learning solutions with market needs and drive innovation. 

Publish research findings in top-tier conferences such as ICASSP, WASPAA, ICLR, and contribute to the academic and professional community. 

Document and present findings and results to stakeholders. 

Required 

MSc / PhD degree in Computer Science, Artificial Intelligence, Deep Learning, or related discipline. 

Experience in successfully completing deep learning projects for audio, acoustics, or Music Information Retrieval. 

Proficiency in programming languages (e.g. Python, C++) 

Proficiency with deep learning frameworks (TensorFlow, PyTorch) 

Strong understanding of neural networks, CNNs, LSTMs, transformers, and other deep learning architectures. 

Familiarity with data preprocessing techniques and tools for audio data and room acoustics. 

Excellent problem-solving skills and attention to detail. 

Strong communication and teamwork skills. 

Preferred 

Knowledge of generative models, diffusion models and speech processing 

A passion for Audio and Music. 

Publications or contributions to the deep learning and audio processing community. 

Experience with cloud platforms such as Azure, AWS, or Google Cloud. 

Familiarity with Agile methodologies and tools such as JIRA.

Location 

London, UK (hybrid: 3 days a week in office, plus occasional travels)