Product Lead, Learning Technology

Speak · San Francisco

  • Senior
  • Full-time
  • $191,000 – $315,000
  • Posted 2026-11-09
  • Confirmed live on 10 November 2026

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Job description

ABOUT US

Our mission is to reinvent the way people learn, starting with language.

Learning a language can change a life by opening doors to new cultures, careers, and communities. Two billion people around the world are actively trying to learn a language, but the best way to learn (one-on-one tutoring) is hard to access at scale and hasn’t been meaningfully improved in decades. Speak is building a human-level, AI-powered tutor in your pocket: a conversation-first experience that lets learners actually speak, get instant feedback, and progress through carefully designed lessons. The result is a complete path from beginner to confident speaker across multiple languages.

Speak first launched in South Korea in 2019, where Speak has now become the number one language learning app, and we now serve learners across many markets and 15+ languages. Speak is one of the world’s leading AI companies, with over $150m raised in venture investment from OpenAI, Accel, Founders Fund, Khosla Ventures, and more, with a distributed team across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.

ABOUT THIS ROLE

Speak is building an AI tutor that remembers useful context across lessons, responds naturally to learner speech, and adapts what it teaches. Making this work reliably across languages and proficiency levels requires more than one model: it depends on voice technology, learner memory, generated content, evaluation, and the systems that put them together.

We're hiring a Product Lead for Learning Technology to own product direction across these capabilities. You'll work directly with our founders, engineering and research leaders, and the teams building Speak's Tutor to decide where to use external models, improve existing systems, or develop technology of our own — and which investments will actually improve the learner experience.

This is a hands-on product leadership role. You'll build and lead PMs across Voice ML, AI Platform, Content Quality, and Memory while remaining involved in the most important technical product decisions. Initially, you'll take direct responsibility for priority areas that lack dedicated PM ownership, particularly shared AI systems and evaluations.

WHAT YOU'LL BE DOING

- Own Learning Technology product direction and investment choices across voice, AI platform and evaluations, learner memory, and generated-content quality.

- Work with Core Learning to identify which changes in model behavior, lesson quality, personalization, or real-time interaction would most improve Tutor use and learning.

- Decide when to adopt a new model, fine-tune one, build a specialized capability, or use an external service, weighing quality, latency, reliability, and cost.

- Shape evaluation and release decisions for learner speech and real-time voice, including ASR, TTS, and new conversational models. Connect model benchmarks to performance in actual lessons and conversations.

- Set product requirements for the Tutor agent harness, model-serving and shared AI tooling, prioritizing the reliability and capabilities product teams need over unnecessary platform work.

- Work with Content Quality and Learning Design to improve generated lessons, curriculum inputs, and content evaluations. Keep teaching standards and learner-facing teaching decisions with the teams that own them.

- Take promising research and prototypes through integration, production measurement, and iteration; make the build, buy, extend, or stop decision when evidence arrives.

- Hire, coach, and manage PMs who can independently own technical product areas and make consequential decisions without routing everything through you.

WHAT WE'RE LOOKING FOR

If you don't meet every criterion below but are excited about the role, please apply. Technical founders, engineers who moved into product, and leaders of user-facing AI products can all have relevant backgrounds.

Must-have qualifications

- Deep technical product experience with AI/ML or similarly complex systems. You can reason about model behavior, data, evaluations, failure modes, reliability, latency, and cost well enough to make decisions with engineers.

- Evidence of personally taking a technical capability, research effort, or prototype into production, with measurable product or business impact.

- Strong product judgment, including connecting technical improvements to user experience and deciding what to build, buy, adapt, or stop.

- Experience leading multiple related product areas, making priorities and tradeoffs clear, and delivering results through other teams.

- Direct experience hiring, managing, and developing PMs, including delegating real ownership, coaching, and performance management.

- Clear communication and the ability to work directly with highly technical teams, researchers, and company leadership.

Nice-to-have qualifications

- Experience with LLMs, agents, memory, personalization, or recommendation systems.

- Experience with ASR, TTS, r

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