Senior Staff Research Scientist at DeepL leading innovation in speech and multilingual translation models. Working collaboratively on cutting-edge language AI technologies while mentoring a diverse team.
Responsibilities
Lead hands-on research and development across ASR, MT, TTS, and speech-to-speech translation for real-time voice products.
Design, train, and optimize large-scale ASR models for multilingual accuracy, robustness, and ultra-low-latency streaming.
Improve cascaded translation pipelines end to end: segmentation, ASR→MT interfaces, streaming MT inference, and incremental decoding.
Develop and refine real-time TTS models with natural prosody, stable speaker characteristics, and fast inference.
Build and experiment with end-to-end and LLM-based speech-to-speech translation systems, including streaming and one-shot approaches.
Own the full lifecycle of model delivery: prototyping, ablations, training, evaluation, optimization, and production deployment.
Work closely with engineering teams to integrate models into real-time systems, ensuring reliability, uptime, and quality at scale.
Drive improvements in inference efficiency, model serving, voice UX, and robustness to real-world acoustic conditions.
Establish strong practices for evaluation, reproducibility, monitoring, and continuous model improvement in production.
Mentor researchers and engineers, promote hands-on collaboration, and raise the bar for model quality and operational excellence.
Requirements
Deep expertise in speech, audio, or multilingual ML, particularly in ASR, MT, TTS, end-to-end ST, or large speech models.
A hands-on builder who enjoys training models, running experiments, debugging pipelines, and integrating ML systems into production.
Strong understanding of real-time streaming constraints and how to design models that operate reliably at low latency.
Experience shipping ML models to production, maintaining them at scale, and working with engineers on deployment, monitoring, and serving.
Ability to lead complex research efforts while staying grounded in product impact, user experience, and real-world performance.
Strong coding and experimentation skills (Python, PyTorch/JAX, audio processing libraries).
Ability to communicate clearly, collaborate across teams, and align research work with product and engineering priorities.
Proven experience mentoring others and elevating technical quality across a fast-moving, applied research team.
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