Роль сочетает исследования ML с запуском решений в продакшен в быстроразвивающейся сфере Voice AI, но зарплата ниже рыночного ориентира, а описание указывает на высокий темп и постоянные изменения.
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TL;DR
Machine Learning Researcher (Voice AI): Improving production voice AI models and systems through evaluation, data curation, fine-tuning, and rapid deployment with an accent on speech-to-text, text-to-speech, voice agents, and customer-focused model quality. Focus on identifying model limitations, designing meaningful benchmarks, solving customer problems with deep learning, and shipping reliable improvements to production within weeks.
Location: USA — Remote; New York City, NY; San Francisco, CA
Base salary: $150K–$250K annually. Equity and a 10% annual bonus may also be offered; these are not included in the base salary range.
Company
Deepgram provides real-time voice AI APIs and self-hosted or on-premises software for speech-to-text, text-to-speech, and production voice agents.
What you will do
Identify where voice AI models fall short and set measurable improvement targets.
Design evaluations and benchmarks to determine whether models improve and why.
Curate and generate data, fine-tune deep learning models, and use external models where appropriate.
Build working voice AI systems quickly and ship them to production for customers.
Address customer problems including language and regional expansion, pronunciation, speaker isolation, steerable and cloned voices, and other voice capabilities.
Own customer problems end to end and determine when results are ready for production.
Requirements
Deep experience training, fine-tuning, and evaluating deep learning models.
Strong Python and PyTorch skills.
A track record of shipping machine learning systems to production.
Experience owning problems end to end and learning what is needed to solve them.
Good judgment about which problems matter and when a result is ready to ship.
Ability to translate vague customer problems into clear metrics and find fast, effective solutions.
No specific degree is required; demonstrate difficult problems solved through past projects, shipped systems, or open-source work.
Nice to have
Experience with speech-to-text, text-to-speech, or voice agents.
Experience with distributed training.
Published papers, open-source contributions, or public benchmarks.
Culture & Benefits
AI use and comfort are core expectations for every role.
Use and experiment with advanced AI tools and integrate them into daily work.
Work in a rapidly changing environment that requires experimentation, adaptability, and continuous learning.
Equity and a 10% annual bonus may be offered in addition to base salary.
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