Research Staff – Voice AI Foundations

🔥 1 minute ago

🇦🇺 Australia – Remote

⏰ Full Time

🔴 Lead

🤖 Artificial Intelligence

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Deepgram

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 $47M Series B on 2022-11

Consulting • Healthcare • Logistics

Deepgram is a leading voice AI company that provides powerful APIs for speech-to-text, text-to-speech, and language understanding applications. Their platform enables developers to build sophisticated voice AI solutions for use cases such as contact centers, medical transcription, conversational AI, and more. Known for unmatched accuracy, speed, and cost-effectiveness, Deepgram's technology is trusted by top enterprises and startups worldwide. By offering real-time and highly accurate transcription capabilities, Deepgram helps businesses gain insights from voice data, making it an essential tool for transforming voice interactions.

📋 Description

• Develop next-generation neural audio codecs with extreme low-bit-rate compression and high-fidelity reconstruction • Pioneer steerable generative models for diverse human speech, including emotional, multi-speaker, noisy, and overlapping-speech scenarios • Develop embedding systems that factorize latent representations into speaker, content, style, environment, and channel dimensions • Use latent recombination to generate synthetic audio data at previously impossible scales • Train multimodal speech-to-speech systems for robust understanding and empathic human-like responses • Design model architectures, training schemes, and inference algorithms optimized for bare-metal hardware • Enable cost-efficient training on billion-hour datasets and real-time inference for hundreds of millions of concurrent conversations • Conduct rigorous controlled experiments, ablations, evaluations, stress tests, and edge-case analyses • Contribute to foundational research advancing voice AI, speech, and language modeling

🎯 Requirements

• Strong mathematical foundation in statistical learning theory, particularly self-supervised and multimodal learning • Deep expertise in foundation model architectures and scaling training across multiple modalities • Ability to derive novel mathematical formulations and implement them efficiently • Demonstrated ability to build and curate massive datasets while maintaining quality and diversity • Track record of designing controlled experiments to validate architectural innovations and theoretical insights • Experience optimizing models for real-world deployment, including hardware constraints and efficiency techniques • History of open-source contributions or research publications advancing speech/language AI • Comfort actively using and experimenting with advanced AI tools • Ability to identify critical experiments that validate or disprove ideas quickly • Vision to scale successful proofs-of-concept 100x • Experience or knowledge relevant to neural audio codecs, generative models, embedding systems, latent representations, multimodal speech-to-speech systems, model architectures, training schemes, inference algorithms, and hardware-efficient deployment

🏖️ Benefits

• Remote work arrangement • AI-first work environment with encouragement to use and experiment with advanced AI tools • Opportunity to work on transformative voice AI research at scale • Open-source contribution and research publication opportunities • AI Notetaker interview recording can be declined without affecting candidacy