Senior Audio AI Research Engineer

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.

The Team and The Role

Do you want to shape the future of video collaboration and redefine what it means to communicate, connect, and create? Logitech is at the forefront of Audio AI innovation, combining creative design, innovative science, and cutting‑edge technology to deliver exceptional communication experiences. Imagine your work being at the heart of conference rooms across the globe, used by thousands every day, including over 350 companies in the Fortune 500. We’re on a mission: to make virtual communication so seamless and powerful that it’s better than being there in person. As part of our growing Real‑time Audio AI Team, you’ll play a pivotal role in shaping Logitech’s leadership in AI for best‑in‑class, real‑time audio experiences. By leveraging state‑of‑the‑art multi‑modal AI technologies, your impact will resonate on a global scale.

Why Join Us?

At Logitech, we combine the agility of a small team with the power of a global organization. We’re passionate about what we do, we use the products we build, and we prioritise innovation and connection. This is an opportunity to join an ambitious and collaborative team that thrives on solving complex challenges and having fun doing it. This role is part of a new initiative to grow an Audio AI lab in London. You will be supported by both a Senior Technical Manager and Principal Engineer in Audio AI, and collaborate with PhD‑level interns working on parallel research tracks.

Your Contribution

As a Senior Audio AI Research Engineer, you will help explore and mature Audio AI solutions, combining technologies, enhancing their robustness, and solving complex problems prior to their productisation. We’re looking for someone inventive, who can prototype and trial novel algorithms, combining prior internal research, open‑source contributions, and their own ideas to create novel user experiences. This role offers the chance to collaborate with some of the best research institutions for AI and Audio worldwide, such as EPFL, Hamburg, and Berkeley Universities.

Here’s how you’ll make an impact:

• Explore innovative ways to leverage the company’s distinctive strengths in video conferencing. This includes optimizing the use of distributed microphone arrays and cameras, each precisely mapped with location and orientation data.
• Utilise participant identification and positioning, as well as multiple video and audio streams within a given space.
• Address complex challenges before deploying new Audio AI technologies. This involves optimizing integration with other components in the Audio AI pipeline, identifying the most effective task combinations, and developing strategies to minimise bias while enhancing robustness against noise, reverberation, and echo.
• Conduct in‑depth research to address emerging challenges in Audio AI, including the development of multi‑modal solutions that integrate audio, video, and other sensor data.
• Develop advanced audio streaming solutions for low‑latency, real‑time causal AI systems.
• Focus on evolving technologies from earlier research stages to deployment‑ready maturity, collaborating with other teams responsible for quantisation, deployment, and C++ optimisation.
• Demonstrate the ability to rapidly prototype Audio AI technologies by implementing research papers and extending them—such as modifying data augmentation strategies, adjusting FFT parameters, incorporating auxiliary tasks, and optimising loss functions.
• Experience with data‑driven algorithm tuning using metadata evaluations and advanced acoustic simulations is highly desirable.

Hard Skills

• Comprehensive knowledge of latest AI advancements, such as diffusion, flow matching, transformers, and GANs.
• 4+ years of experience in machine learning frameworks (TensorFlow/PyTorch) with a proven history of building ML pipelines in the audio domain.
• Proficiency in Python, including package development and collaborative coding practices (e.g., open‑source contributions).
• Expertise in performance analysis and optimisation of ML systems.
• Hands‑on deployment experience with systems like TensorFlow Lite, ONNX, TVM, and Glow.
• Strong familiarity with cloud compute environments, ideally AWS, and data ingestion (e.g., TF Data pipelines).
• Knowledge of source control and project tracking systems (e.g., GitHub, Jira).

Preferred Experience

• Track record of research publications in conferences such as ICASSP and Interspeech.
• Knowledge of Audio Engineering and Acoustics.
• Sound understanding of embedded systems and constraints.

Soft Skills

• Passionate about team collaboration, valuing collective success over individual output.
• Research collaboration across academia and industry.
• Excellent attention to detail, alongside pragmatic problem‑solving.
• Self‑starter with the ability to conduct independent research and refine priorities efficiently.
• Open to feedback, with a hunger to grow professionally and personally.
• Strong communication and time‑management skills to deliver impact in a fast‑paced environment.

Qualifications

• PhD or equivalent experience in Computer Science, Audio/Acoustics, Electrical Engineering, Physics, or related fields.
• BSc, MSc, or Ph.D.