Senior Staff Research Scientist | Voice in Bonn

Overview

In this role you lead scientific innovation in real-time speech and translation models at DeepL Voice. You define long-term scientific strategy, prototype rapidly, and run large-scale experiments that push production-ready breakthroughs. You’ll work across ASR, MT, TTS, and speech-to-speech translation, shaping end-to-end and end-to-end-to-end approaches for multilingual, low-latency systems. You operate at the intersection of research and product impact, collaborating with engineering to scale reliable, high-quality voice solutions. This is a high-visibility opportunity to influence the next generation of speech and multimodal translation technology at a fast-moving AI company.

Verantwortungsbereiche

• Lead hands-on R&D across ASR, MT, TTS, and speech-to-speech translation for real-time voice products
• Design, train, and optimize large-scale multilingual ASR models with ultra-low-latency streaming
• Improve end-to-end translation pipelines including segmentation, interfaces, streaming MT, and decoding
• Develop real-time TTS models with natural prosody and fast inference
• Build and evaluate end-to-end and LLM-based speech-to-speech translation systems with streaming and one-shot approaches
• Own the full lifecycle of model delivery from prototyping to production deployment
• Collaborate with engineering to integrate models into real-time systems ensuring reliability and quality
• Drive efficiency, model serving, voice UX, and robustness to real-world acoustic conditions
• Establish evaluation, reproducibility, monitoring, and continuous improvement in production
• Mentor researchers and engineers to raise technical quality and collaboration

Zentrale Anforderungen

• Deep expertise in speech, audio, or multilingual ML (ASR, MT, TTS, end-to-end ST, or large speech models)
• Hands-on experience training models, running experiments, debugging pipelines, and productionizing ML systems
• Strong understanding of real-time streaming constraints and low-latency design
• Experience shipping ML models to production and working with deployment, monitoring, and serving teams
• Ability to lead complex research with focus on product impact and user experience
• Strong coding and experimentation skills (Python, PyTorch/JAX, audio processing libraries)
• Clear communication and cross-team collaboration, aligning research with product priorities
• Proven experience mentoring others and elevating technical quality

• communication
• collaboration
• mentoring
• Python
• PyTorch
• JAX