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. We’re looking for an Audio Data Infrastructure Engineer to design and maintain a robust, scalable data pipeline that transforms raw audio from diverse sources into structured analytics at scale.
In this role, you’ll own the database architecture, high-volume ingestion pipelines, and analysis and labeling workflows that process many terabytes of audio. This includes ingesting raw audio, running large-scale ML- and DSP-based analysis, and storing the resulting metadata and analytics efficiently in a large PostgreSQL database.
Design scalable ingestion pipelines for audio data from many sources.
Build distributed compute pipelines for ML inference on audio frames.
Design and maintain efficient metadata storage for audio, frames, statistics, and analysis results.
3+ years of experience in Data Engineering, ML Infrastructure, or Distributed Systems, working on production systems at scale.
~ Strong Python engineering skills, including async processing, multiprocessing, and large-scale batch workflows.
~ Practical familiarity with audio data as a modality, including common processing tools (e.g. FFmpeg) and an understanding of how audio artifacts and preprocessing choices affect downstream analysis.
~ A startup mindset : Prior startup or similarly dynamic experience is a strong plus.
Benefits
Opportunity to work at a rapidly growing Voice AI startup, backed by top investors.
Competitive salary package, additional benefits and stock options, enabling you to take part in the company’s success.
Startup Culture: 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.
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.