Applied ML Manager

Posted 18 Days Ago
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San Francisco, CA
Hybrid
250K-300K Annually
Senior level
Edtech
The Role
Manage and grow the ML team, define goals and metrics, drive ML initiatives, build evaluation processes, and collaborate cross-functionally to enhance product delivery.
Summary Generated by Built In
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

We’re looking for an ML Manager to lead our ML team (currently 4 people across voice ML and broader ML systems) and raise the bar on execution, measurement, and strategy.

This is a hands-on manager role: you’ll be the line manager for the team, partner closely with Andrew to set direction and ambition, and help us consistently ship ML improvements that move product metrics. You’ll also help us expand and pressure test our strategy as new modeling approaches emerge (for example, speech-to-speech), while keeping the team focused on high-impact bets.

What you’ll be doing
  • Manage and grow the ML team through clear expectations, regular feedback, and strong coaching.

  • Define quarterly ML goals and success metrics, establish baselines, and build a visible “scoreboard” for progress.

  • Drive end-to-end execution on key ML initiatives: planning, evaluation, iteration, rollout, and impact measurement.

  • Build a repeatable model evaluation and experimentation process (quality, performance, reliability), including rollout criteria.

  • Partner with Product and Engineering leaders to align roadmaps, clarify ownership, and ensure ML work is shippable and predictable.

  • Identify gaps in our current ML strategy, propose concrete bets, and translate direction into actionable plans.

  • Help hire thoughtfully as the team grows, without prematurely scaling into a large org.

What we’re looking for
  • 8–10+ years overall experience in applied ML, with a track record of shipping ML and LLM systems into production.

  • 4+ years people management experience, including leading 1:1s, giving feedback, and handling performance.

  • Strong technical judgment in applied ML (not primarily ML infra/MLOps), including ability to define and run rigorous evaluations.

  • Excellent metric sense and analytical thinking: can translate ambiguous goals into measurable outcomes and make tradeoffs.

  • Strong cross-functional collaboration skills with Product, Engineering, and Design.

  • Clear written communication: can write crisp strategy docs, decision memos, and goal docs.

  • Bonus: speech/audio, linguistics, or multimodal experience.

Why work at Speak
  1. Join a fantastic, tight-knit team at the right time: we're growing very quickly, we've most recently raised our Series C from some of the top investors in the valley, and we've achieved product-market fit in our initial markets. You'd join at a magical time when a single person could significantly change the course of the company.

  2. Do your life's work with people you’ll love working with: we care strongly about our craft and want every person at Speak to feel like they're growing every day. We believe in the idea that working with people you both enjoy and have respect for makes everything better. We hire thoughtfully and only work with people we admire deeply.

  3. Global in nature: We're live in over 40 countries and launching in a number of new markets soon. We have dedicated offices in San Francisco, Ljubljana, Seoul, and Tokyo, and you’ll have the opportunity to talk to users in each of these regions on a regular basis as well as travel.

  4. Impact people's lives in a major way: Learning a language is one of the single most life-changing skills one can learn, and right now 99% of people never achieve their goal because the process is broken. We’re helping millions of people achieve their goals and improve their lives.

Speak does not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Top Skills

Experimentation Processes
Llm Systems
Machine Learning
Model Evaluation
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The Company
San Francisco, CA
191 Employees

What We Do

Speak is a language learning app that sets users on the path to fluency with the world’s most advanced AI tutor. Built on the core learning philosophy of getting users speaking out loud as much as possible, Speak's AI language-learning experience encourages dynamic two-way dialogue through personalized content and real-time speech recognition.

Speak was founded by Connor Zwick and Andrew Hsu in 2016 to democratize access to high quality language education through AI. Backed by Y Combinator, Open AI, Founders Fund, Khosla Ventures, Matrix Partners and more, Speak is a series B startup with a global presence and offices in San Francisco, Seoul, Tokyo, and Ljubljana.

Featured by Apple as the ‘App of the Day’ and ‘Best New App’, Speak is hiring across the globe. Come join us as we teach the next billion people English and reinvent the way the world learns, staring with language

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