Auf einen Blick
- Aufgaben: Collect and analyze audio datasets for machine learning training and evaluation.
- Arbeitgeber: Join ai|coustics, a Berlin startup revolutionizing Generative Audio AI technology.
- Mitarbeitervorteile: Enjoy competitive pay, stock options, and learning opportunities in a dynamic startup culture.
- Warum dieser Job: Shape the future of audio tech while working with passionate innovators in a collaborative environment.
- Gewünschte Qualifikationen: Expertise in audio processing, Python coding, and machine learning concepts required.
- Andere Informationen: Ideal start date is January 15, 2025; be part of a groundbreaking growth stage.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
About usai-coustics is building the reliability layer for Voice AI, the system that closes the gap between raw audio input and reliable machine understanding in production. By combining state-of-the-art speech and audio research with real-time, production-grade SDKs, we test, observe, and enable Voice AI systems to work in any environment.Our software is used by Voice AI companies across Europe and the United States whose products require reliable performance at scale: call center agents, voice agents, telephony apps, and enterprise voice assistants. We believe voice will become the main interface for technology and ai-coustics is building the foundational infrastructure to make audio input reliable, measurable, and easy to deploy.We are backed by leading early-stage investors including Connect Ventures, Partech, Inovia Capital, as well as angel investors from HuggingFace, DeepMind and Amazon with deep expertise in AI and developer infrastructure. These partners share our vision and are helping us build a world-class team operating with high levels of responsibility and velocity. We look for people who take ownership, think systemically, and want to solve challenging real-world problems in close collaboration with our customers. If you\’re motivated by developing technology that is used in practice, shaping an emerging category and setting a new standard for how Voice AI works in the real world, you\’ll feel at home at ai-coustics.Role overviewAs an Audio Data Engineer at ai-coustics, you will own the data foundations that power our speech and audio enhancement models. Your work sits at the intersection of audio signal processing, large-scale data pipelines, and machine learning, and directly impacts model quality, reliability, and real-world performance.You will design, build, and maintain systems for collecting, processing, curating, and evaluating large volumes of audio data across diverse real-world conditions. This includes creating high-quality datasets, defining evaluation and benchmarking pipelines, and working closely with ML researchers and engineers to translate raw audio into measurable model improvements.TasksCollect, process, manage, and analyze large-scale audio datasets for ML training and evaluation.Design, maintain, and continuously improve data augmentation pipelines.Develop and enhance tools and protocols for perceptual and quantitative evaluation.Stay up-to-date on current research related to your role (e.g., non-intrusive and perceptual speech metrics, open-source datasets, pre-trained audio ML models).Serve as the primary expert on all things data, sharing your knowledge and providing context to the team.RequirementsYou are an audio and speech expert:You have a deep understanding of audio processing, psychoacoustics, and the audio signal chainYou know how to measure audio and speech quality quantitativelyYou are an expert listener, and you can confidently identify common audio and speech artifacts and distortionsYou are a skilled engineer:You are proficient in Python and write clean, well-documented, and maintainable codeYou are familiar with modern software development tools and workflowsYou know how to use standard audio processing tools e.g. (ffmpeg, librosa), and you understand and can quickly integrate ML-based audio toolsYou have a solid understanding of data structures and algorithms, and you know your way around modern data bases and common cloud platformsYou have a solid math and machine learning background:You have a deep mathematical understanding of digital signal processingYou have a solid understanding of modern machine learning concepts, in particular neural networks.You are well versed in exploratory data analysisYou are up to date with the scientific literature, understand new concepts quickly and can gauge the usefulness of approaches and tools.BenefitsOpportunity to work at a rapidly growing Voice AI startup, backed by top investors.Compensation and equity: Competitive salary package, additional benefits and stock options, enabling you to take part in the company\’s success.Startup Culture: Dynamic, fast-paced environment with passionate and collaborative colleagues.High Impact: Groundbreaking startup at a pivotal growth stage, making a real difference in how people experience audio.Ownership & Autonomy: Take full ownership of projects and ship fast.Work With the Best: World-class team of engineers and builders with ample room for professional growth.Contribute to the Future: Define the landscape of Voice AI technology.If you are ready to lead the charge in revolutionizing Voice AI and drive our startup to new heights, we would love to hear from you. Apply today to join the ai-coustics team
Audio Data Engineer Arbeitgeber: ai-coustics
Kontaktperson:
ai-coustics HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Audio Data Engineer
✨Tip Number 1
Familiarize yourself with the latest trends in audio processing and machine learning. Follow relevant research papers and industry news to stay updated, as this knowledge will help you stand out during discussions with our team.
✨Tip Number 2
Showcase your hands-on experience with audio processing tools like ffmpeg and librosa. If you have personal projects or contributions to open-source software, be ready to discuss them in detail, as practical experience is highly valued.
✨Tip Number 3
Prepare to demonstrate your problem-solving skills related to audio quality measurement. Think of specific examples where you've identified and resolved audio artifacts, as this will highlight your expertise in the field.
✨Tip Number 4
Engage with our community on platforms like GitHub or LinkedIn. Networking with current employees or contributing to discussions about audio technology can give you insights into our company culture and values, making your application more compelling.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Audio Data Engineer
Tipps für deine Bewerbung 🫡
Understand the Company: Dive deep into ai|coustics and their mission. Familiarize yourself with their Generative Audio AI technology and how it impacts various industries. This knowledge will help you tailor your application to align with their goals.
Highlight Relevant Experience: Make sure to emphasize your expertise in audio processing, psychoacoustics, and machine learning. Provide specific examples of projects or experiences that showcase your skills in these areas.
Showcase Technical Skills: Clearly outline your proficiency in Python and any audio processing tools you've used, such as ffmpeg or librosa. Mention your experience with data structures, algorithms, and cloud platforms to demonstrate your engineering capabilities.
Express Passion for Innovation: Convey your enthusiasm for working in a startup environment and your commitment to advancing audio technology. Share any relevant research or literature you've engaged with to show your dedication to staying current in the field.
Wie du dich auf ein Vorstellungsgespräch bei ai-coustics vorbereitest
✨Show Your Passion for Audio Technology
Make sure to express your enthusiasm for audio processing and speech enhancement during the interview. Share specific examples of projects or experiences that highlight your passion and expertise in this field.
✨Demonstrate Your Technical Skills
Be prepared to discuss your proficiency in Python and any relevant audio processing tools like ffmpeg and librosa. You might be asked to solve a technical problem or explain your approach to data management and analysis, so brush up on your coding skills and be ready to showcase your knowledge.
✨Stay Updated on Current Research
Since the role requires staying current with research related to audio metrics and machine learning, mention any recent papers or developments you've followed. This shows your commitment to continuous learning and your ability to integrate new concepts into your work.
✨Prepare for Behavioral Questions
Expect questions about teamwork and collaboration, especially since you'll be sharing your expertise with the team. Think of examples that demonstrate your ability to work well in a startup environment and how you handle challenges or conflicts.