Research Engineer, Machine Learning Systems

Deepgram is a leading platform for the Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and production-grade voice agents. Over 200,000 developers and 1,300+ organizations build voice offerings powered by Deepgram, including Twilio, Cloudflare, Sierra, and others. Deepgram's voice-native foundation models are accessed via cloud APIs or self-hosted/on-premises software, with a focus on accuracy, low latency, and cost efficiency. Backed by a recent Series C, Deepgram has processed over 50,000 years of audio and transcribed over 1 trillion words.

Deepgram is seeking a highly skilled and versatile Machine Learning Engineer to join the Research team. As a Member of the Research Staff, you will partner with research scientists to prototype and validate novel modeling ideas, then scale them through robust training systems for speech technologies, internal tooling, and innovative data strategies. You'll work at the intersection of machine learning, data infrastructure, and internal tooling to support the mission of building world-class speech recognition and synthesis systems.

• Architect and manage horizontally scalable systems that accelerate the end-to-end training lifecycle for Speech-to-Text (STT) and Text-to-Speech (TTS) models, including optimized data preparation, high-throughput training pipelines, distributed infrastructure, and automated evaluation tooling.
• Design and implement internal UIs and tools that make ML systems and workflows accessible to non-technical stakeholders.
• Oversee and manage training tooling, job orchestration, experiment tracking, and data storage.

• Strong experience with the machine learning research pipeline, particularly in STT or related speech domains, including experimenting with new architectures and implementing large-scale training systems.
• Proficiency with orchestration and infrastructure tools like Kubernetes, Docker, and Prefect.
• Familiarity with ML lifecycle tools such as MLflow.
• Experience building internal tools or dashboards for non-technical users.
• Hands-on experience with data engineering practices for unstructured audio and text data.
• Comfortable working in cross-functional teams including researchers, engineers, and product stakeholders.

Estimated base salary $150K – $250K, with equity and a 10% annual bonus.

Apply through the provided Ashby application link.