Audio AI & Digital Signal Processing Engineer

Blue Signal Search
London
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer, Amazon Studios AI Lab

Data Scientist

Data Engineer

Lead / Senior Software Engineer - ML/AI

Strategic Finance Analyst

Data Analyst Lead - AdTech

Title:Audio AI & Digital Signal Processing Engineer


Company Overview:

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.

The Opportunity:

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.


About Blue Signal:

Blue Signal is a leading executive search firm, specializing in engineering recruitment. Our engineering recruiting team has expertise placing high-performing talent in areas such as electrical, mechanical, civil, and telecom engineering. Learn more atbit.ly/46IAFRJ

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Jobs

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Jobs

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.