Audio ML Researcher — Real-Time TTS & STT Expert

Bland; United States; Remote; USD 160,000 - 250,000; Full time

Benefits offered by this job

Healthcare

Equity

Tools for success

SF office with rooftop views

Job summary

Bland seeks a Machine Learning Researcher focusing on audio to advance voice technologies from speech-to-text to expressive text-to-speech. You will work on foundational models, training at enterprise scale, and deploying inference systems for millions of calls per day.

The role emphasizes building scalable pipelines, rigorous experiments, and collaboration with engineering teams to turn research into production-ready voice solutions.

Qualifications

• Experience with self-supervised learning, multimodal modeling, or generative modeling.
• Hands-on experience building or scaling TTS, STT, or neural audio codec systems.
• Familiarity with large-scale speech datasets and real-world audio variability.

Responsibilities

• Design and scale next-generation TTS models with expressive output.
• Develop neural audio codec-based architectures for high-fidelity generation.
• Improve prosody, emotion, and multi-speaker robustness for real-time inference.
• Build and scale ASR systems robust to accents, noise, and telephony artifacts.
• Research and implement neural codecs for efficient compression and controllable synthesis.
• Create scalable training pipelines across distributed GPU clusters.

Skills

Self-supervised learning

Multimodal modeling

Generative modeling

TTS systems

STT systems

Neural audio codecs

Distributed training

Job description

Bland seeks a Machine Learning Researcher focusing on audio to advance voice technologies from speech-to-text to expressive text-to-speech. You will work on foundational models, training at enterprise scale, and deploying inference systems for millions of calls per day.

The role emphasizes building scalable pipelines, rigorous experiments, and collaboration with engineering teams to turn research into production-ready voice solutions.