Senior ML Engineer - Speech (m/f/d)

voize

5d•Hybrid

About The Position

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! 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.

Requirements

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

Responsibilities

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.