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For Companies At a Glance
- Tasks: Shape the future of audio tech by analysing and translating sound into insights.
- Company: Join a growing tech team focused on innovative audio-driven products.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in audio machine learning and influence core technology.
- Qualifications: Strong background in audio ML or signal processing; PhD or MSc preferred.
- Other info: Fast-paced environment with ownership over projects and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
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
Audio Machine Learning Engineer employer: Enterprise Recruitment Ltd
Contact Detail:
Enterprise Recruitment Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Audio Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the audio machine learning space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to audio ML. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of acoustic challenges and be ready to discuss how you’d tackle them. Confidence and clarity can really set you apart.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. It shows initiative and enthusiasm!
We think you need these skills to ace Audio Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in audio machine learning and applied signal processing. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about audio-driven products and how your background makes you a perfect fit for our team. Let us know what excites you about this opportunity!
Showcase Your Technical Skills: Don’t forget to mention your experience with modern ML tooling and any challenges you've tackled in real-world acoustic environments. We love seeing practical examples of how you’ve applied your knowledge in previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Enterprise Recruitment Ltd
✨Know Your Audio ML Fundamentals
Brush up on your core knowledge of audio machine learning and applied signal processing. Be ready to discuss specific techniques you've used, such as model training and evaluation, and how they relate to real-world acoustic challenges like noise and reverberation.
✨Showcase Your Project Experience
Prepare to talk about your previous projects, especially those involving dataset strategy and model design. Highlight any experience you have with edge or embedded ML optimisation, as this will demonstrate your hands-on skills and understanding of the full lifecycle of audio intelligence.
✨Demonstrate Team Collaboration Skills
Since you'll be working in a small, fast-moving team, it's crucial to show that you can collaborate effectively. Share examples of how you've worked alongside hardware and software specialists in the past, and how you contributed to achieving common goals.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's audio-driven products and their approach to tackling acoustic challenges. This not only shows your genuine interest in the role but also gives you a chance to assess if the company aligns with your career aspirations.
