Note: The job is a remote job and is open to candidates in USA. Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT) and text-to-speech (TTS). They are seeking a highly skilled Machine Learning Engineer to join their Research team, where the role involves prototyping and validating novel modeling ideas and scaling them through robust training systems for speech technologies.
Responsibilities
- Architect and manage horizontally scalable systems that dramatically accelerate the end-to-end training lifecycle for Speech-to-Text (STT) and Text-to-Speech (TTS) models
- Design and implement internal UIs and tools that make ML systems and workflows accessible to non-technical stakeholders across the company
- Oversee and manage training tooling, job orchestration, experiment tracking, and data storage
Skills
- Strong experience with the machine learning research pipeline, particularly in STT or related speech domains. This includes experimenting with and evaluating new architectures and modeling approaches, 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 that include researchers, engineers, and product stakeholders
Benefits
- Medical, dental, vision benefits
- Annual wellness stipend
- Mental health support
- Life, STD, LTD Income Insurance Plans
- Unlimited PTO
- Generous paid parental leave
- Flexible schedule
- 12 Paid US company holidays
- Quarterly personal productivity stipend
- One-time stipend for home office upgrades
- 401(k) plan with company match
- Tax Savings Programs
- Learning / Education stipend
- Participation in talks and conferences
- Employee Resource Groups
- AI enablement workshops / sessions
- For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.
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