Machine Learning and Artificial Intelligence Research Placement

Based:High Wycombe
Term:Full-time, 12-month placement
Salary:£23500 pa

Role Description

We are seeking a passionate, curiosity-driven AI & Machine Learning Researcher to explore cutting-edge AI & ML applications within a music-making context. You will work closely with our Product, Design and Engineering teams to discover, evaluate, and propose implementations of AI & ML-driven solutions for creative tools in both software and embedded environments. 

This role is ideal for a placement student or an individual early in their career, who is keen to dive into AI and Machine Learning trends within the audio and music industry. Your key responsibilities will include researching emerging AI projects, assessing their relevance and feasibility for music and audio applications, and helping us experiment with new possibilities in sound synthesis, sound discovery, generative music, and beyond. 

Core Responsibilities Include:

• Conduct research on AI and machine learning projects relevant to music production, sound generation, and audio technology. 
• Explore potential applications such as sound synthesis, sound management, resynthesis, and generative music tools. 
• Run pre-trained AI models from platforms like Hugging Face and evaluate their potential in music and audio contexts. 
• Collaborate with cross-functional teams (Product, Design, and Development) to propose AI-driven solutions and features. 
• Stay updated with AI trends, tools, and models, especially those impacting the music and audio industry. 
• Assess feasibility and practicality of AI applications for integration into Novation's products and workflows. 
• Create technical reports, presentations, and demonstrations of your findings. 

What We’re Looking For:

• A strong curiosity and passion for AI and machine learning, particularly in their applications within the music and audio industry. 
• Some experience or familiarity with running AI/ML models (e.g., Hugging Face) and working with related technologies. 
• An understanding of machine learning basics, including neural networks, generative models, and deep learning techniques. 
• Interest in creative music technologies, sound design, and audio software. 
• Problem-solving mindset, with the ability to think critically and propose practical solutions based on research. 
• Strong communication skills to articulate technical findings and collaborate with multidisciplinary teams. 

Bonus Skills: 

• Experience with programming languages such as Python or familiarity with ML frameworks (e.g., TensorFlow, PyTorch). 
• Knowledge of audio processing, music production tools, or embedded systems. 
• Familiarity with digital signal processing (DSP) concepts or sound design. 

About Us

Doing a 12-month placement at Focusrite is like becoming one of the family. A rapidly growing, global family. We’re focused on providing opportunities for everyone and anyone to enjoy creating music.

Our placements are very popular, and that’s mainly because you can really get stuck in during your year with us. We don’t ask you to answer the phones and do the photocopying. We want you to help develop our products, market our brands, speak to our customers and make us better. A lot of our previous placements candidates are now full-time employees.

All placements last for 12-months. We pay you £23500 per year (£25650 for London-based roles), and you get to share some of the same benefits as our permanent employees.

Our brands, Focusrite, Focusrite Pro, Novation, Ampify, ADAM Audio, Martin Audio, Optimal Audio, Linea Research, Sequential, Oberheim, Sonnox, OutBoard and TiMax come together around a common mission to remove barriers to creativity.

We work hard. We are professional. And we play hard too. We select really, really talented and passionate people. And we absolutely love our work. So if you think you can bring something new to the mix, we look forward to hearing from you.

Please apply for as many of our placements as you wish.

Timetable for applications:

Deadline