About us
ai-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 overview
We’re looking for a Machine Learning Intern with a strong background in deep learning and hands-on experience in audio and speech processing. You’ll work on applied research and development tasks closely aligned with the core machine learning algorithms behind our products, contributing to models, data pipelines, and evaluation under the guidance of experienced engineers and researchers.
This role is aimed at PhD students or exceptionally strong Master’s students who want to gain hands-on industry and startup experience working on real-world audio machine learning systems. The internship is on-site in Berlin and must last at least 6 months.
Tasks
- Model development & deployment: Design, implement, train, evaluate, optimize, and deploy deep learning models for speech enhancement and related audio problems.
- Data-centric machine learning: Build, curate, and refine custom datasets and complex audio simulation pipelines for training and evaluation to understand and improve model performance for real-world production use cases.
- MLOps & tooling: Help us to continuously improve our internal tools, pipelines, and infrastructure to accelerate iteration and ensure reliability.
- Demonstrating value: Collaborate with sales and developer relations on case studies, documentation, demos, and technical content.
Requirements
- You are a PhD student or an exceptionally strong Master’s student, with demonstrated research experience and publications in relevant venues (e.g. NeurIPS, ICML, ICLR, Interspeech, ICASSP, WASPAA, ASRU, or related workshops and journals).
- Hands-on experience applying machine learning to audio and speech, with prior work on speech enhancement, source separation, ASR, TTS, speaker-related tasks, or closely related audio ML problems.
Benefits
- Opportunity to work at a rapidly growing Voice AI startup, backed by top investors.
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!
