Research Staff, Machine Learning Engineer - Remote

Overview

Deepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than Deepgram

In Short

• Join Deepgram as a Machine Learning Engineer focusing on scalable training systems for speech technologies.
• Work on building internal tools and driving innovation in data strategies.
• Architect and manage training systems for STT and TTS models.
• Design internal UIs and tools for non-technical stakeholders.
• Oversee training tooling, job orchestration, and data storage.
• Identify critical experiments for validating ideas quickly.
• Collaborate with researchers, engineers, and product stakeholders.
• Strong experience in training large-scale machine learning systems required.
• Proficiency with orchestration tools like Kubernetes and Docker is essential.
• Contribute to shaping the future of human-machine communication.

Requirements

• Strong experience in training large-scale machine learning systems, particularly in STT or related speech domains.
• 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 that include researchers, engineers, and product stakeholders.

Benefits

• Shape the future of human–machine communication.
• Prioritize ownership, experimentation, and real-world impact in research culture.
• Empowered to build tools and systems that accelerate ML research.
• Opportunity to work on cutting-edge technology.
• Significant impact in the AI industry.
• Equal opportunity employer with a focus on collaboration and customer-first approach.
• Accommodations available for applicants who need them.