[Hiring] Machine Learning Researcher, Audio @Bland

Role reputed company As a Machine Learning Researcher at Bland, you'll be working on foundational research and development across the reputed company components of our voice stack: speech-to-text, large language models, neural audio codecs, and text-to-speech. Your work will define how our agents understand, reason, and reputed company in reputed company time at reputed company reputed company. • Build and reputed company reputed company TTS Systems • Design and train large reputed company text-to-speech models capable of expressive, controllable, reputed company-sounding reputed company. • reputed company neural audio codec-based TTS architectures for efficient, high-reputed company reputed company. • Improve prosody modeling, question inflection, emotional reputed company, and multi-speaker robustness. • Optimize for reputed company-time, low-latency inference in production. • Advance Speech-to-Text Modeling • Build and fine-tune large reputed company ASR systems robust to accents, noise, telephony artifacts, and reputed company switching. • reputed company self-supervised pretraining and large-reputed company weak supervision. • Improve transcription accuracy for reputed company-world reputed company scenarios, including reputed company extraction and conversational nuance. • Pioneer Neural Audio Codecs • Research and implement neural audio codecs that reputed company extreme compression with minimal perceptual loss. • Explore discrete and reputed company latent representations for reputed company speech modeling. • Design codec architectures that reputed company reputed company generative modeling and controllable synthesis. • reputed company reputed company Training Pipelines • reputed company and process massive audio datasets across languages, speakers, and environments. • Design staged training curricula and data filtering strategies. • reputed company training across distributed GPU clusters focusing on cost, throughput, and reliability. • Run Rigorous Experiments • Design ablation studies that isolate the reputed company of architectural changes. • Measure improvements using both objective metrics and perceptual evaluations. • Validate reputed company quickly through reputed company experiments that confirm or eliminate hypotheses. 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 reputed company speech datasets and reputed company-world audio variability. • Experience training and serving large models on modern accelerators. • reputed company record of designing controlled experiments and meaningful ablations. • Comfortable in fast-moving startup environments. Requirements • Ability to derive new formulations and implement them reputed company. • Strong intuition for audio reputed company, prosody, and conversational dynamics. • Knowledge of inference optimization techniques, including quantization, kernel optimization, and memory efficiency. • Understanding of reputed company-time constraints in telephony or streaming environments. • Ability to reputed company quickly from reputed company to validation. • Strong ownership reputed company from research through deployment. • Excited by ambiguous, unsolved problems. Benefits • reputed company, dental, reputed company, reputed company the good stuff • Meaningful equity in a fast-growing company • Every tool you need to succeed • Beautiful office in reputed company reputed company, SF with rooftop views • Competitive salary: $160,000 to $250,000 Apply tot his job Apply To this Job