Deepgram

6 months ago

Research Staff, Voice AI Foundations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Research Staff role focused on pioneering Latent Space Models for advanced Voice AI. Expected to develop next-gen neural codecs, steerable generative models for speech, and scalable embedding systems, while designing hardware-efficient training and inference for billions of conversations. You’ll work in a fast-paced, AI-first environment shaping foundational research and contributing to practical, scalable AI systems.

Location: California, Ann Arbor, San Francisco

Workplace: Remote

Employment Type: Full time · Permanent

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Pioneer development of Latent Space Models (LSMs) to address data, scale, and cost challenges in robust voice AI systems.
•Research and develop solutions for problems including next-generation neural audio codecs, steerable generative models for diverse speech, and embedding systems with interpretable latent dimensions.
•Design model architectures, training schemes, and inference algorithms optimized for hardware at bare metal, enabling cost-efficient training on billion-hour datasets and real-time inference for hundreds of millions of conversations.
•Build and manage data pipelines to curate massive, diverse audio datasets suitable for training, evaluation, and benchmarking of new models.
•Collaborate across teams to validate theories with rigorous experiments, publish findings, and contribute to open-source efforts when applicable.

Pay and Benefits

Salary: USD 150,000 - 250,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kPaid LeaveLearning BudgetRemote WorkHome Office

Key Requirements

•Strong mathematical foundation in statistical learning theory, particularly in areas relevant to self-supervised and multimodal learning
•Deep expertise in foundation model architectures, with an understanding of how to scale training across multiple modalities
•Proven ability to bridge theory and practice—someone who can both derive novel mathematical formulations and implement them efficiently
•Demonstrated ability to build data pipelines that can process and curate massive datasets while maintaining quality and diversity
•Track record of designing controlled experiments that isolate the impact of architectural innovations and validate theoretical insights

Experience:Voice AISpeechMachine learning

Skills:CommunicationCollaborationProblem-solvingCritical thinkingCreative

Languages:English

Tech Stack:PythonMachine learningDeep learningLatent space modelsNeural networks

Company Brief

Deepgram

Deepgram builds a real-time Voice AI platform delivering speech-to-text, text-to-speech, and voice-agent APIs for developers and enterprises, focusing on low-latency, high-accuracy voice models and scalable deployment options.

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor

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Deepgram

6 months ago

Research Staff, Voice AI Foundations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: California, Ann Arbor, San Francisco

Workplace: Remote

Employment Type: Full time · Permanent

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Pioneer development of Latent Space Models (LSMs) to address data, scale, and cost challenges in robust voice AI systems.
•Research and develop solutions for problems including next-generation neural audio codecs, steerable generative models for diverse speech, and embedding systems with interpretable latent dimensions.
•Design model architectures, training schemes, and inference algorithms optimized for hardware at bare metal, enabling cost-efficient training on billion-hour datasets and real-time inference for hundreds of millions of conversations.
•Build and manage data pipelines to curate massive, diverse audio datasets suitable for training, evaluation, and benchmarking of new models.
•Collaborate across teams to validate theories with rigorous experiments, publish findings, and contribute to open-source efforts when applicable.

Pay and Benefits

Salary: USD 150,000 - 250,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kPaid LeaveLearning BudgetRemote WorkHome Office

Key Requirements

•Strong mathematical foundation in statistical learning theory, particularly in areas relevant to self-supervised and multimodal learning
•Deep expertise in foundation model architectures, with an understanding of how to scale training across multiple modalities
•Proven ability to bridge theory and practice—someone who can both derive novel mathematical formulations and implement them efficiently
•Demonstrated ability to build data pipelines that can process and curate massive datasets while maintaining quality and diversity
•Track record of designing controlled experiments that isolate the impact of architectural innovations and validate theoretical insights

Experience:Voice AISpeechMachine learning

Skills:CommunicationCollaborationProblem-solvingCritical thinkingCreative

Languages:English

Tech Stack:PythonMachine learningDeep learningLatent space modelsNeural networks

Company Brief

Deepgram

Industry: API Platforms

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2015

Glassdoor: 4.5

Website LinkedIn Glassdoor