Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop cutting-edge deep learning models for audio projects like source separation and signal enhancement.
- Company: L-Acoustics is a leader in premium sound reinforcement technologies, enhancing shared sound experiences.
- Benefits: Enjoy a hybrid work model, with 3 days in the office and occasional travel opportunities.
- Why this job: Join a passionate team shaping the future of sound in the live music industry.
- Qualifications: MSc/PhD in Computer Science or related field; experience in deep learning for audio required.
- Other info: Contribute to top-tier conferences and collaborate with cross-functional teams.
The predicted salary is between 36000 - 60000 £ per year.
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)
Deep Learning Engineer employer: L-Acoustics
Contact Detail:
L-Acoustics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Deep Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in deep learning, particularly in audio processing. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your passion for audio and music by participating in relevant online communities or forums. Engaging with others in the field can provide insights and connections that may lead to opportunities at L-Acoustics.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those related to audio and deep learning. Be ready to explain your thought process, challenges faced, and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 4
Network with professionals in the audio and deep learning sectors. Attend industry conferences or webinars where you can meet potential colleagues from L-Acoustics and learn more about their work culture and expectations.
We think you need these skills to ace Deep Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in deep learning, audio projects, and any specific technologies mentioned in the job description. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for audio and music, as well as your understanding of deep learning applications in this field. Mention specific projects or experiences that align with L-Acoustics' mission and values.
Showcase Your Projects: If you have completed any deep learning projects related to audio, be sure to include them in your application. Provide links to your work or a portfolio that demonstrates your skills and contributions to the field.
Prepare for Technical Questions: Anticipate technical questions related to deep learning frameworks, model evaluation, and audio processing techniques. Brush up on your knowledge of neural networks and be ready to discuss your problem-solving approach in detail.
How to prepare for a job interview at L-Acoustics
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deep learning frameworks like TensorFlow and PyTorch. Bring examples of past projects, especially those related to audio processing, to demonstrate your proficiency.
✨Understand the Company’s Mission
Familiarise yourself with L-Acoustics' commitment to shaping the future of sound. Be ready to explain how your skills and experiences align with their mission and how you can contribute to their innovative audio solutions.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process when tackling challenges in deep learning, particularly in audio projects, to showcase your analytical skills.
✨Communicate Effectively
Strong communication is key, especially when collaborating with cross-functional teams. Practice articulating complex concepts clearly and concisely, as you'll need to present findings to stakeholders and contribute to team discussions.
