Applied Linguist (Hourly)

Position Overview

• Location Type: Remote
• Job Type: Contract

Company 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.

Deepgram is looking for an Applied Linguist to elevate the quality, authenticity, and usability of our multilingual speech AI products—including STT, TTS, and voice agents. You’ll go beyond language availability to ensure our global offerings are accurate, expressive, and culturally attuned. From conversational cues to regional norms, you’ll help shape how Deepgram understands and interacts with the world’s languages. This includes curating and analyzing linguistic data, designing culturally sensitive benchmarks, collaborating with native speakers and domain experts, and partnering cross-functionally with product, research, and engineering. If you’re passionate about linguistics, technology, and building truly global products, this is a high-impact role at the intersection of all three.

What You’ll Do

• Develop and maintain linguistic datasets that power multilingual features (e.g., formatting, fillers, entity recognition, culturally-based formalities).
• Design culturally and linguistically grounded benchmarking frameworks for our AI products and systems.
• Analyze language-specific model behaviors and guide improvements based on linguistic diagnostics.
• Coordinate with native speakers, localization experts, and contractors to ensure naturalness and cultural appropriateness.
• Create and maintain annotation guidelines, pronunciation lexicons, and text normalization rules.
• Work with Data Operations and Labeling teams to ensure multilingual labeling quality.
• Partner with Research and Product to test new languages and features from a linguistic perspective.
• Provide ongoing QA for multilingual models and contribute to internal documentation for model behavior.

You’ll Love This Role If You

• Believe that great AI must understand everyone, everywhere.
• Are energized by the challenge of making speech technology work well across many languages.
• Take pride in linguistic detail and know how to scale language support with practical creativity.
• Thrive on collaboration with engineers, researchers, and annotators alike.
• Get joy from seeing your linguistic decisions reflected in live products used by global customers.

It’s Important To Us That You Have

• A degree in Linguistics, Computational Linguistics, NLP, a related field, or proven experience working in these fields.
• Hands-on experience creating or curating language resources (e.g., corpora, lexicons, annotation guidelines) for applied use.
• Working knowledge of multiple languages or a demonstrated ability to analyze unfamiliar linguistic systems quickly and effectively.
• Practical experience writing, maintaining, and debugging tools for linguistic data analysis—using Python, regular expressions, and libraries like Pandas, spaCy, or NLTK.
• Comfort using LLMs or other AI tools to prototype, extend, or refine linguistic workflows.
• Experience with text normalization, transliteration, and standardization of mixed-language scenarios (e.g., Spanglish, code-switching) in real-world product applications.
• A track record of contributing to or improving team-owned tools, workflows, or pipelines.
• Strong written and verbal communication skills, especially when collaborating with cross-functional teams.