Senior Audio AI Research Engineer

Overview

In this role you will advance Audio AI research to deliver robust, real-time, multi-modal audio-visual solutions for Logitech’s video conferencing. You join a London-based AI lab that collaborates with top research institutions, shaping products used in global conference spaces. You will prototype and mature novel algorithms, integrating audio, video and sensors to reduce bias and latency. This opportunity offers high-impact work at the intersection of academia and industry, with a focus on innovative user experiences.

Pay / Benefits

• comprehensive and competitive benefits packages
• hybrid work model / remote work options
• focus on wellbeing (physical, financial, emotional, intellectual, social)
• collaboration-friendly, inclusive culture
• global exposure and cross-team learning
• flexible and supportive working environments

Responsibilities

• Prototype and evaluate novel Audio AI algorithms and multi-modal solutions
• Optimize integration within the Audio AI pipeline and balance task combinations for robustness
• Develop multi-modal systems combining audio, video and sensor data
• Build low-latency, real-time audio streaming solutions and evolve deployment-ready maturity
• Rapidly prototype by adapting research papers and extending them with data augmentation, FFT tuning, and loss function optimization
• Collaborate with academia and industry researchers (e.g., EPFL, Hamburg, Berkeley)
• Contribute to research-to-product handoffs including quantization and C++ optimization
• address bias and noise/reverberation/echo challenges before productization
• leverage distributed microphone arrays and camera mappings with position/orientation data

Key requirements

• 4+ years of ML experience in audio domain
• Proficiency in Python and ML frameworks (TensorFlow/PyTorch)
• Hands-on deployment with TensorFlow Lite, ONNX, TVM, Glow
• Strong performance analysis and optimization of ML systems
• Experience with cloud environments (AWS) and TF Data pipelines
• Knowledge of GitHub and Jira for code and project tracking
• Track record of research publications (ICASSP, Interspeech) is preferred
• Embedded systems knowledge and acoustics understanding
• PhD or equivalent in CS/Audio/EE/Physics or related fields

• team collaboration and willingness to share success
• independent researcher with strong prioritization
• attention to detail and pragmatic problem solving
• diffusion, flow matching, transformers, GANs
• ML pipelines in audio (TensorFlow/PyTorch)
• Python package development

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