INTERNSHIP DETAILS
ML Internship
Companyai-coustics
LocationBerlin
Work ModeOn Site
PostedJanuary 11, 2026

Internship Information
Core Responsibilities
The intern will work on model development and deployment, focusing on designing, implementing, training, and evaluating deep learning models for audio problems. They will also build and refine datasets and improve internal tools and pipelines.
Internship Type
intern
Company Size
29
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Voice AI that stands out from the noise.
Real-time, AI-powered speech enhancement solutions. Ready to scale, for small teams and enterprise alike.
About the Role
<p><strong>About us</strong></p>
<p>ai-coustics is building the <strong>reliability layer for Voice AI,</strong> 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.<br>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 <strong>voice will become the main interface for technology</strong> and ai-coustics is building the foundational infrastructure to make audio input reliable, measurable, and easy to deploy.</p>
<p>We are backed by <strong>leading early-stage investors</strong> including <strong>Connect Ventures, Partech, Inovia Capital</strong>, as well as angel investors from <strong>HuggingFace, DeepMind</strong> and <strong>Amazon</strong> with deep expertise in AI and developer infrastructure. These partners share our vision and are helping us build a world-class team operating with <strong>high levels of responsibility and velocity</strong>. 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.</p>
<p><strong>Role overview</strong></p>
<p>We’re looking for a <strong>Machine Learning Intern</strong> with a strong background in deep <strong>learning</strong> and <strong>hands-on experience in audio and speech processing</strong>. You’ll work on <strong>applied research and development tasks</strong> 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.</p>
<p>This role is aimed at <strong>PhD students</strong> or <strong>exceptionally strong Master’s students</strong> who want to gain <strong>hands-on industry and startup experience</strong> working on real-world audio machine learning systems. The internship is <strong>on-site in Berlin</strong> and <strong>must last at least 6 months</strong>.</p>
<h2 id="tasks">Tasks</h2>
<ul>
<li><strong>Model development & deployment</strong>: Design, implement, train, evaluate, optimize, and deploy deep learning models for speech enhancement and related audio problems.</li>
<li><strong>Data-centric machine learning</strong>: 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.</li>
<li><strong>MLOps & tooling</strong>: Help us to continuously improve our internal tools, pipelines, and infrastructure to accelerate iteration and ensure reliability.</li>
<li><strong>Demonstrating value</strong>: Collaborate with sales and developer relations on case studies, documentation, demos, and technical content.</li>
</ul>
<h2 id="requirements">Requirements</h2>
<ul>
<li>You are a <strong>PhD student</strong> or an <strong>exceptionally strong Master’s student</strong>, with demonstrated research experience and publications in relevant venues (e.g. NeurIPS, ICML, ICLR, Interspeech, ICASSP, WASPAA, ASRU, or related workshops and journals).</li>
<li><strong>Hands-on experience applying machine learning to audio and speech</strong>, with prior work on speech enhancement, source separation, ASR, TTS, speaker-related tasks, or closely related audio ML problems.</li>
<li><strong>Expert-level proficiency with PyTorch</strong> and its ecosystem as well as familiarity with cloud-based training setups, experiment tracking tools, and modern development practices. You write clean, modular, production-ready code.</li>
<li><strong>A startup mindset:</strong> You’re comfortable with ambiguity, proactive in open-ended settings, and motivated to work on practical machine learning problems in a fast-paced, product-driven environment.</li>
</ul>
<h2 id="benefits">Benefits</h2>
<ul>
<li>Opportunity to work at a <strong>rapidly growing Voice AI startup</strong>, backed by top investors.</li>
<li><strong>Compensation and equity:</strong> Competitive salary package, additional benefits and stock options, enabling you to take part in the company’s success.</li>
<li><strong>Startup Culture:</strong> Dynamic, fast-paced environment with passionate and collaborative colleagues.</li>
<li><strong>High Impact:</strong> Groundbreaking startup at a pivotal growth stage, making a real difference in how people experience audio.</li>
<li><strong>Ownership & Autonomy:</strong> Take full ownership of projects and ship fast.</li>
<li><strong>Work With the Best:</strong> World-class team of engineers and builders with ample room for professional growth.</li>
<li><strong>Contribute to the Future:</strong> Define the landscape of Voice AI technology.</li>
</ul>
<p>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!</p>
Key Skills
Machine LearningDeep LearningAudio ProcessingSpeech ProcessingPyTorchMLOpsData PipelinesModel DevelopmentSpeech EnhancementSource SeparationASRTTSTechnical DocumentationCollaborationResearch ExperienceProduction-Ready Code
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