Audio Machine Learning Engineer

Covent Garden

2 months ago

Applications closed

Audio Machine Learning Engineer

A growing technology team is developing a new generation of intelligent, audio-driven products designed to interpret real-world acoustic environments and generate meaningful insight. As development accelerates, they are seeking an Audio Machine Learning Engineer to shape how sound is analysed, classified, and translated into useful information across edge and cloud platforms.

The Opportunity Working alongside embedded, hardware, and software specialists, you will contribute to the full lifecycle of audio intelligence, from dataset strategy and model design through to optimisation and deployment.

The role offers genuine ownership and the chance to influence core technology within a product-focused engineering environment.

Required:

Core experience

Strong grounding in audio machine learning or applied signal processing
Experience training and evaluating models using modern ML tooling
Awareness of real-world acoustic challenges such as noise, reverberation, and variability
Comfort working in a small, fast-moving engineering team
Likely a PhD or MSc + some industry experience
Beneficial

Edge or embedded ML optimisation
Audio feature extraction or DSP knowledge
Postgraduate study in a relevant technical discipline
Experience with sensing, monitoring, or real-world data systems

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Apr 8, 2026

Products

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

Mar 24, 2026

Jobs

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

Feb 9, 2026

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.