Deepgram
51 - 200 employees
Founded 2015
đŒ Consulting
đ„ Healthcare
đŠ Logistics
đ° $47M Series B on 2022-11
Consulting âą Healthcare âą 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.
Applied ML Engineer
đ July 9
đșđž United States â Remote
đ” $150k - $220k / year
â° Full Time
đĄ Mid-level
đ Senior
đ€ Machine Learning Engineer
đŠ H1B Visa Sponsor
đ» Ghost score 18%
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Deepgram
51 - 200 employees
Founded 2015
đŒ Consulting
đ„ Healthcare
đŠ Logistics
đ° $47M Series B on 2022-11
Consulting âą Healthcare âą 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.
đ Description
âą Own the research-to-production pipeline âą Partner directly with research scientists to productionize new models âą Build and extend the tooling and abstractions âą Design and own model release gates âą Optimize models and serving for production âą Strengthen the build and delivery layer for models âą Establish benchmarking and validation âą Build the feedback loop
đŻ Requirements
âą Strong software engineering fundamentals âą Proficiency in Python âą Hands-on experience taking ML models from research or prototype stage into production at scale âą A working understanding of the modern deep learning stack (e.g., PyTorch) âą Experience building ML pipelines and tooling âą Familiarity with serving and inference optimization âą Comfort operating across distributed systems and GPU compute âą A collaborative, builder mindset
đïž Benefits
âą Offers Equity âą Offers Bonus âą 10% Annual Bonus
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