Machine Learning Engineer, ai-coustics, DE

About ai|coustics

At ai|coustics, we’re building the quality layer for Voice AI. Our AI-powered speech technology turns any audio - live or recorded - into studio-quality output in real time. Since our launch, we’ve built a community of over 500,000 users , have processed more than 2 million audio files and signed contracts with leading audio brands like Elgato, Radio France International or Deutsche Welle .

We recently closed our 5M Seed round with leading investors like Partech and Connect Ventures alongside Inovia Capital, FOV Ventures, Intuition and Arc Investors. We’re at a pivotal moment of growth and product innovation - and we’re looking for ambitious builders to join us on this journey. If you’re excited about defining a new category in Voice AI and shaping the future of audio, we’d love to meet you.

Who we are

We’re an in-person team of audio and technology enthusiasts based out of Berlin . We love being in the office, hanging out together and learning from each other everyday.

We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. Our culture thrives on autonomy, ownership, and open collaboration - where the best ideas win, no matter where they come from.

We support each other. We have an open and inclusive culture that’s focused on giving everyone the resources they need to succeed.

About the role

We’re looking for a Machine Learning Engineer with a passion for audio, a strong track record of training and deploying models, and the drive to create real-world impact—beyond just papers and benchmarks. Join a small, focused team building the core algorithms behind our products , where you'll take full ownership of the machine learning lifecycle

Tasks

• Model development & deployment : Design, train, evaluate, optimize, and deploy deep learning models for speech enhancement—and more. Our work spans both lightweight models for edge devices and high-performance models for the cloud.
• Data-centric development : Build, curate, and refine training datasets and simulation pipelines. Develop robust evaluation frameworks to drive model performance.
• MLOps & Tooling : Help us continuously improve our internal tools, pipelines, and infrastructure to accelerate iteration and ensure reliability.

Requirements

• 3+ years of hands-on experience building and iterating on custom deep learning models, ideally in a startup or product-centric environment.
• Strong expertise in audio and speech processing —you understand the quirks, challenges, and beauty of sound. Ideally you have experience in audio sequence-to-sequence modelling and got your hands dirty working on speech enhancement, speech-to-text, text-to-speech or similar.
• Expert-level proficiency with PyTorch and its ecosystem.
• Familiarity with cloud-based training setups , experiment tracking tools , and modern development practices . You write clean, modular, production-ready code.
• A startup mindset : You’re comfortable with ambiguity, move fast when it matters, take initiative, and focus on building, shipping, and winning customers.

Benefits

• Competitive Compensation: Enjoy a competitive salary package and additional benefits.
• Stock Options: Early-stage employees receive stock options, enabling you to share in the company’s success.
• Learning Opportunities: Collaborate with a team of accomplished audio and ML experts, with ample room for professional growth.
• Startup Culture: Immerse yourself in a dynamic, fast-paced environment with passionate and collaborative colleagues.
• Professional Growth: Seize the chance to shape your career path as the company expands.
• High Impact: Join a groundbreaking startup at a pivotal growth stage, making a real difference in how people experience audio.
• Contribute to the Future: Help define the landscape of generative audio and speech enhancement technology.

If you are ready to lead the charge in revolutionizing the audio experience and drive our startup to new heights, we would love to hear from you. Apply today to join the ai-coustics team!