Senior ML Engineer - Speech (m/f/d)
Summary
Senior Machine Learning Engineer who designs, trains, evaluates, and deploys speech recognition (ASR/STT) deep learning models used in voize's AI companion for frontline workers, shipping fast inference on mobile and hosted environments. Core stack is Python and PyTorch, with end-to-end ownership from research to production and monitoring.
🎤 Why voize? Because we’re more than just a job!
At voize, we believe the greatest gift to frontline workers is time - time to care, connect, and be present. Today, that time is lost to busywork and complex systems that pull them away from what matters most: people.
Our vision is to change that by building AI companions that seamlessly take over digital workflows. We don’t replace humans with technology - we amplify their impact.
Our mission is backed with a $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs. Today, 2,000+ facilities trust voize, and over 200,000 users rely on our AI companion to ease their daily workload.
As a dynamic team, we combine first-in-class technology with meaningful social impact. And now, we’re looking for you to join us on this mission!
💡 Your Mission
If you're a Machine Learning Engineer experienced with Speech recognition and are excited to work at the cutting edge of product design, applied ML research, and MLOps, then go ahead and apply! With us, you'll build products with direct user feedback, train AI models with real data, and ship new features to production every day.
🚀 Your Daily Business - No two days are alike
Take ownership for the design, training, evaluation, and deployment of our deep learning models in the space of speech recognition
The models you build and refine are at the heart of our applications and directly impact the end-user
You'll improve a diverse family of speech models live in the field, across languages and products, and engineer fast inference on mobile devices and in hosted environments.
🤝 Your Skillset - What you bring to the table
Several years hands-on experience in Deep Learning for speech recognition, including developing and optimising ASR-systems (not just academic research)
Excellent foundation in STT (Speech-to-Text) system development with a focus on real-world applications
Experience with owning the ML process end-to-end: from concept and exploration, to model productionization, maintenance, monitoring and optimization
Shipped ML models to production with Python and PyTorch
Strong software engineering: clean code, tests, guardrails
🌱 Growing together - what you can expect at voize
We are a fast-growing startup, that means you will tackle challenges, grow quickly, and make a real impact, giving frontline workers more time for people
We foster an open, collaborative culture with regular team events, whether you work from our Berlin office or remotely across Germany
Become a co-creator of our success with stock options
Generous perks: 30 vacation days plus your birthday off, Germany Transport Ticket, Urban Sports Club, regular company off-sites, and access to learning platforms such as Blinkist and Audible, plus free language courses
You decide when you work best, that means flexible working hours and a good hybrid set-up.
✨ Ready to talk? Apply now! 🚀
We look forward to your application and can’t wait to meet you - no matter who you are or what background you have!
Skills
As published by ashby · 10 questions · 1 written answer
Basics
Resume, Name, Email
Short answers (4)
- What is your LinkedIn?
- What city are you currently based in?
- What is your salary expectation? (gross annual, EUR)
- What is your notice period?
Pick from a list (5)
- Are you proficient in German or French?
- Do you currently have the legal right to work in Germany/Poland (e.g., citizenship, permanent residence, or have avalid work visa)?
- What’s your preferred work setup?
- How many years of hands-on experience do you have building ASR/STT systems?
- Which of these have you done in production, not just in research?
Written answers (1)
- Describe an ASR or speech model you took from idea to production. What was your role, what was the measurable impact (e.g., WER, latency), and what went wrong along the way? (max ~150 words)
