Research Engineer – Machine Learning Systems
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Job Description
Machine Learning Engineer at Deepgram prototyping novel modeling ideas to build scalable speech technologies. Collaborate with researchers to develop world-class speech recognition and synthesis systems.
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.
Requirements:
- 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
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