Hybrid Senior Staff Research Scientist – Voice

at DeepL

• Job title: Senior Staff Research Scientist – Voice
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Python, PyTorch
• Location requirements: Hybrid, London, United Kingdom

About the role

• 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.

Benefits

• Competitive benefits
• Open and welcoming work culture