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- 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 and groundbreaking projects.
- Qualifications: Master's or Ph.D. in relevant fields with strong DSP and machine learning skills 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.
- 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.
- 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.
- 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.
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 genuine interest in 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 about job openings and may even result in referrals, increasing your chances of landing the role.
✨Tip Number 3
Showcase your practical skills by working on personal projects related to audio AI and DSP. Create a portfolio that highlights your experience with programming languages like Python and C++, as well as any deep learning frameworks you've used. This hands-on experience can set you apart from other candidates.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving questions specific to audio signal processing and machine learning. Use platforms like LeetCode or HackerRank to sharpen your coding skills. Being well-prepared will boost your confidence and help you perform better during the interview process.
We think you need these skills to ace Audio AI & Digital Signal Processing Engineer
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 that demonstrate your proficiency in audio technology and programming languages like Python, C++, and MATLAB.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for audio technology and AI. Mention any relevant experience with generative AI models and your understanding of real-time audio processing techniques. Be sure to explain why you want to work with this innovative company.
Showcase Relevant Projects: If you have worked on projects involving audio signal processing or machine learning, include them in your application. Provide links to any relevant work, such as GitHub repositories or published papers, to demonstrate your expertise.
Highlight Collaboration Skills: Since the role involves working with interdisciplinary teams, emphasise your communication and collaboration skills. Share examples of how you've successfully worked in cross-functional environments to achieve project goals.
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. Practice explaining your thought process when solving complex issues related to audio processing and model optimisation.
✨Highlight Collaboration Experience
Since the role involves working with interdisciplinary teams, share examples of successful collaborations. Emphasise your communication skills and how you've contributed to team projects in the past.
