Audio AI & Digital Signal Processing Engineer
Audio AI & Digital Signal Processing Engineer

Audio AI & Digital Signal Processing Engineer

Bradford Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and optimise algorithms for audio signal processing and generative AI models.
  • Company: Join an innovative leader in AI-driven audio technology, shaping the future of sound.
  • Benefits: Enjoy flexible remote work, competitive pay, and opportunities for travel and collaboration.
  • Why this job: Be at the forefront of audio innovation with a high-impact team in a fast-paced environment.
  • Qualifications: Master's or Ph.D. in relevant fields; strong DSP and machine learning background required.
  • Other info: This role offers a chance to influence the future of AI-powered audio solutions.

The predicted salary is between 43200 - 72000 £ per year.

Our client is an innovative leader in AI-driven audio technology, pioneering advancements in digital signal processing (DSP) and generative AI. With a cutting-edge approach to watermarking, forensic analysis, and sound synthesis, this company is shaping the future of audio authenticity and AI-powered content creation. Their rapidly growing team collaborates with some of the biggest names in the entertainment, media, and technology sectors.

We are seeking a highly skilled Audio AI & DSP Engineer to drive innovation in audio signal processing and machine learning applications. This is an opportunity to work at the forefront of AI-generated sound, audio watermarking, and forensic analysis in a fast-paced, high-impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications.

Key Responsibilities:
  • Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction.
  • Design and train generative AI models to create, process, and analyze audio content.
  • Implement and refine AI-based forensic audio analysis and watermarking techniques to ensure authenticity and attribution.
  • Collaborate with interdisciplinary teams to manage and preprocess large datasets for AI training.
  • Optimize model performance for real-time inference and scalability in production environments.
  • Stay at the cutting edge of research and technological advancements in audio AI, DSP, and machine learning.
  • Provide technical leadership and mentorship to junior engineers and research teams.
Required Qualifications:
  • Master's or Ph.D. in Computer Science, Electrical Engineering, Music Technology, or a related field.
  • Strong background in digital signal processing (DSP) and machine learning applied to audio.
  • Proficiency in programming languages such as Python, C++, and MATLAB.
  • Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.).
  • Understanding of real-time and embedded audio processing techniques.
  • Experience working with generative AI models for audio synthesis and transformation.
  • Strong problem-solving skills with the ability to implement robust, efficient, and scalable solutions.
  • Excellent communication and collaboration skills in cross-functional environments.
Preferred Experience:
  • Expertise in neural network architectures and generative adversarial networks (GANs) for audio applications.
  • Knowledge of secure audio processing techniques, watermarking, and cryptographic applications in AI.
  • Experience with cloud-based AI/ML infrastructure for training and deployment.
  • Background in audio engineering, acoustics, or music technology.
Why Join Us?
  • Be part of a high-impact, high-growth team driving innovation in AI-driven audio technology.
  • Collaborate with top-tier professionals in AI, audio engineering, and digital media.
  • Work on groundbreaking projects with direct applications in music, entertainment, and security.
  • Enjoy flexible remote work arrangements with opportunities for travel and collaboration.
  • Competitive compensation package, including salary, performance bonuses, and potential equity.

This is more than just an engineering role—it’s an opportunity to influence the future of AI-powered audio solutions. If you’re passionate about audio technology, machine learning, and creating cutting-edge solutions, we want to hear from you.

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Contact Detail:

Blue Signal Search Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Audio AI & Digital Signal Processing Engineer

✨Tip Number 1

Familiarise yourself with the latest advancements in audio AI and digital signal processing. Follow industry leaders on social media, read relevant research papers, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.

✨Tip Number 2

Network with professionals in the audio technology sector. Attend conferences, webinars, or local meetups focused on AI and DSP. Building connections can lead to valuable insights and potential referrals, increasing your chances of landing the job.

✨Tip Number 3

Showcase your practical experience with projects related to audio processing and machine learning. Whether it's through personal projects, contributions to open-source software, or internships, having tangible examples of your work can set you apart from other candidates.

✨Tip Number 4

Prepare for technical interviews by practising coding challenges and algorithm questions specifically related to audio signal processing. Use platforms like LeetCode or HackerRank to sharpen your skills, ensuring you're ready to tackle any technical assessments during the hiring process.

We think you need these skills to ace Audio AI & Digital Signal Processing Engineer

Digital Signal Processing (DSP)
Machine Learning
Generative AI Models
Audio Watermarking Techniques
Forensic Audio Analysis
Algorithm Development
Python Programming
C++ Programming
MATLAB Proficiency
Deep Learning Frameworks (TensorFlow, PyTorch)
Real-time Audio Processing
Embedded Systems Knowledge
Neural Network Architectures
Generative Adversarial Networks (GANs)
Cloud-based AI/ML Infrastructure
Problem-Solving Skills
Collaboration and Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience in digital signal processing and machine learning. Include specific projects or roles where you've developed algorithms or worked with generative AI models, as these are key to the position.

Craft a Compelling Cover Letter: In your cover letter, express your passion for audio technology and how your skills align with the company's mission. Mention any relevant experience with audio watermarking or forensic analysis, as well as your ability to collaborate in interdisciplinary teams.

Showcase Technical Skills: Clearly list your programming proficiencies, especially in Python, C++, and MATLAB. If you have experience with deep learning frameworks like TensorFlow or PyTorch, make sure to highlight that as well.

Demonstrate Problem-Solving Abilities: Provide examples of past challenges you've faced in audio processing or machine learning projects. Explain how you approached these problems and the solutions you implemented, showcasing your strong problem-solving skills.

How to prepare for a job interview at Blue Signal Search

✨Showcase Your Technical Skills

Be prepared to discuss your experience with digital signal processing and machine learning. Bring examples of algorithms you've developed or optimised, and be ready to explain the technical details behind them.

✨Demonstrate Your Knowledge of AI Models

Familiarise yourself with generative AI models relevant to audio applications. Be ready to discuss how you've implemented these models in past projects and the challenges you faced.

✨Prepare for Problem-Solving Questions

Expect to tackle real-world problems during the interview. Brush up on your problem-solving skills and think through how you would approach issues related to audio signal processing and AI.

✨Highlight Collaboration Experience

Since the role involves working with interdisciplinary teams, be sure to share examples of successful collaborations. Discuss how you communicated complex ideas to non-technical team members and contributed to group projects.

Audio AI & Digital Signal Processing Engineer
Blue Signal Search
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