[Remote] Research Engineer, Machine Learning Systems
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 and text-to-speech. The Research Engineer will partner with research scientists to prototype and validate novel modeling ideas, focusing on scalable model training and tooling 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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