Ready to Train a Mind That’s Not (Yet) Human?
Imagine being called in for a secret mission. A confidential client has entrusted us with something ambitious, strange, and thrilling: building a conversational AI that listens like a human, learns like a scholar, and speaks with purpose. This isn’t a product. It’s a presence. And it’s your chance to help shape it—right at the point where it all begins.
We’re assembling a select team of brilliant minds to work on a newly commissioned, stealth-mode project. The brief? Discreet. The data? One of a kind. The potential? Enormous. We can’t reveal the client’s name (yet), but trust us—when the curtains open, you’ll want to say you were there from the start.
If you’re excited by the unknown, passionate about intelligence (artificial and otherwise), and eager to leave your mark on something world-class and whisper-quiet (for now), then read on.
This isn’t just a job. It’s an origin story.
Role: Speech-to-Text Engineer
The Listener Who Teaches Machines to Hear
In this project, the first heartbeat is audio. And you? You’re the one who translates that heartbeat into language.
As our Speech-to-Text Engineer, you are the conductor between sound and sense—the one who extracts clarity from chaos, and tunes raw audio into structured, high-quality data that will form the backbone of our AI’s mind.
You’ll build the pipelines, fine-tune the engines, and obsess over accuracy like a sound engineer in a studio, knowing that every syllable matters. Because when the machine speaks, it will be because you listened first.
What You’ll Do
– Design and optimize large-scale transcription workflows (hybrid: automated + human QA)
– Set up and refine tools like Whisper, Kaldi, or custom models for diarization, punctuation, and segmentation
– Handle diverse, real-world audio—accents, background noise, overlapping speakers—and turn it into clean, reliable training data
– Automate pre-processing and post-processing workflows to handle thousands of hours of audio
– Collaborate closely with ML engineers to ensure transcripts align with model fine-tuning goals
– Innovate solutions for edge cases and audio anomalies (we want someone who says, “I got this” when the WAVs get weird)
Who You Are
– Deep experience in ASR systems (Automatic Speech Recognition), audio processing, or NLP
– You’ve worked with Whisper, Kaldi, or similar systems and can bend them to your will
– Comfortable working with large datasets and GPU-based processing pipelines
– You care about the details—a misplaced comma, a missed breath, a misattributed speaker all make your eye twitch
– Bonus: background in linguistics, signal processing, or building tools for annotation teams
– Bonus: You secretly wish all meetings were replaced by transcribed voice memos (and you’d build the pipeline for it yourself)
Our Culture & Core Beliefs
We are not building a team of average developers.
We are creating a precision squad of elite builders—the kind who run toward complex challenges, not away from them.
We believe in:
– No rank in the debrief — we speak truth, not title
– Radical accountability — no blame-shifting, no hiding
– Clarity, not noise — our conversations cut through
– Precision execution — good enough is never good enough
– Mutual elevation — we make each other better, or we’re doing it wrong
Our Selection Process
Joining this team means stepping into the big leagues. You’ll face a rigorous process designed to assess not just your skills—but your mindset, your values, and your edge:
– A values & culture interview
– Intelligence and pattern recognition testing
– Deep-dive personality & communication profiling
– A real-world challenge: clean and structure noisy audio data
– Final call with the founders: alignment, culture, future vision
We hire slow. We hire right. We hire for legacy.
Location & Compensation
– Work from our headquarters in Almere, The Netherlands
– We believe in team spirit built in person—like the Blue Angels, we train and fly together
– Pay is well above market average
– If you want Messi or Ronaldo, you don’t lowball.
– We invest in elite talent because this mission deserves nothing less.
If you’re the kind of engineer who wants to whisper to machines until they understand the human voice—join us. The system we’re building will speak because you helped it learn to listen.