About the job
About Us
Our mission is to transform language learning.
Language learning can profoundly impact lives by connecting individuals to new cultures, careers, and communities. With two billion people worldwide striving to learn a language, the most effective method (one-on-one tutoring) remains hard to access at scale and has not seen significant innovation in decades. Speak is pioneering a human-level, AI-driven tutor that fits in your pocket: a conversational-first platform that enables learners to speak, receive immediate feedback, and advance through thoughtfully crafted lessons. The outcome is a comprehensive journey from novice to proficient speaker across various languages.
Since our launch in South Korea in 2019, Speak has ascended to the top of the language learning app market, catering to learners across numerous regions and supporting over 15 languages. Backed by more than $150 million in venture funding from notable investors like OpenAI, Accel, Founders Fund, and Khosla Ventures, we maintain a distributed team across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.
About This Role
In the role of AI Product Engineer at Speak, you will be instrumental in shaping the future of language learning and establishing the most efficient path to fluency. Your key responsibility will be to develop cutting-edge product experiences powered by Language Learning Models (LLMs) and deliver these innovations to millions of users.
Your work will encompass the entire stack and more, including model evaluation, prompt testing, and the development and enhancement of various product features such as conversational onboarding, lesson experiences, grammatical assessment, and personalized learning journeys.
We constantly strive to expand the capabilities of LLMs to provide an extraordinary and unmatched language learning experience for users in over 30 countries worldwide.
Your Responsibilities
Designing and launching LLM-powered language learning products across the full stack, while improving the quality and efficacy of existing AI-driven features at Speak.
Collaborating cross-functionally with Engineering teams, Applied ML, Product, Design, and Content.
Enhancing our process for building LLM applications, including best practices for prompting, experimentation/evaluation, LLM operations, and performance measurement.
Scaling current product features to serve a broader user base and additional languages.

