Research Engineer, Machine Learning Systems
Upload My Resume
Drop here or click to browse · PDF, DOCX, DOC, RTF, TXT
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.
Responsibilities
• Scalable Model Training: 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. This includes far more than automated training: the role focuses on making model development significantly faster and more efficient through optimized data preparation and management, high-throughput training pipelines, distributed infrastructure, and automated evaluation tooling. • Tooling & Accessibility: Design and implement internal UIs and tools that make ML systems and workflows accessible to non-technical stakeholders across the company. These UIs should be designed to provide transparency and flexibility to internally built tooling. • Infrastructure & Tools: Oversee and manage training tooling, job orchestration, experiment tracking, and data storage. • We are seeking Members of the Research Staff who: • See "unsolved" problems as opportunities to pioneer entirely new approaches • Can identify the one critical experiment that will validate or kill an idea in days, not months • Have the vision to scale successful proofs-of-concept 100x • Are obsessed with using AI to automate and amplify your own impact • If you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.
Benefits
• At Deepgram, you’ll help shape the future of human–machine communication. Our research culture prioritizes ownership, experimentation, and real-world impact. As a Member of the Research Staff, you'll be empowered to build tools and systems that accelerate ML research and product deployment at scale. • HOLISTIC HEALTH • Annual wellness stipend • Mental health support • Life, STD, LTD Income Insurance Plans • WORK/LIFE BLEND • 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 • CONTINUOUS LEARNING • 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. • Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!