Machine Learning Researcher, Audio

🔥 6 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $160k - $280k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

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Bland

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

🤖 Artificial Intelligence

🏢 Enterprise

💳 Fintech

Artificial Intelligence • Enterprise • Fintech

Bland is your platform for making ultra-realistic AI phone calls. It enables businesses to create and manage voice interactions with customers efficiently by designing conversational pathways that map out dialogues, set flows, and automate calls 24/7. With features like customizable voice personalities, multilingual support, and seamless integration into existing CRM systems, Bland streamlines communication while ensuring a human-like interaction experience. The platform also offers robust analytics and security measures, making it ideal for enterprises looking to enhance customer engagement.

📋 Description

• Design and train large-scale text-to-speech models capable of expressive, controllable, human-sounding output • Develop neural audio codec-based TTS architectures for efficient, high-fidelity generation • Improve prosody modeling, question inflection, emotional expression, and multi-speaker robustness • Optimize for real-time, low-latency inference in production • Build and fine-tune large-scale ASR systems robust to accents, noise, telephony artifacts, and code switching • Leverage self-supervised pretraining and large-scale weak supervision • Improve transcription accuracy for real-world enterprise scenarios, including structured extraction and conversational nuance • Research and implement neural audio codecs achieving extreme compression with minimal perceptual loss • Explore discrete and continuous latent representations for scalable speech modeling • Design codec architectures enabling downstream generative modeling and controllable synthesis • Curate and process massive audio datasets across languages, speakers, and environments • Design staged training curricula and data filtering strategies • Scale training across distributed GPU clusters with focus on cost, throughput, and reliability • Design ablation studies isolating the impact of architectural changes • Measure improvements using objective metrics and perceptual evaluations • Validate ideas through focused experiments that confirm or eliminate hypotheses • Collaborate with engineering teams to deploy research into production inference systems serving millions of calls per day

🎯 Requirements

• Experience with self-supervised learning, multimodal modeling, or generative modeling • Ability to derive new formulations and implement them efficiently • Hands-on experience building or scaling TTS, STT, or neural audio codec systems • Familiarity with large scale speech datasets and real-world audio variability • Strong intuition for audio quality, prosody, and conversational dynamics • Experience training and serving large models on modern accelerators • Knowledge of inference optimization techniques, including quantization, kernel optimization, and memory efficiency • Understanding of real-time constraints in telephony or streaming environments • Track record of designing controlled experiments and meaningful ablations • Comfortable working with offline benchmarks and live production metrics • Comfortable in fast-moving startup environments • Strong ownership mindset from research through deployment • Experience with large scale distributed training • PhD in ML, AI, or a related field, or equivalent research impact (bonus points) • Research publications or open source contributions in speech or language AI (bonus points) • Background in real-time speech systems or telephony (bonus points)

🏖️ Benefits

• Healthcare • Dental insurance • Vision insurance • Meaningful equity in a fast-growing company • Every tool you need to succeed • Beautiful office in Levi's Plaza, SF with rooftop views

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