Applied ML Engineer, Speech

Speak is revolutionizing language learning through AI-powered conversation technology. As an Applied ML Engineer focused on Speech, you'll join a mission-critical team developing cutting-edge speech recognition models to help millions achieve language fluency.

The role involves end-to-end ownership of ML pipelines - from training and experimenting with ASR models to deployment and monitoring. You'll work closely with Product teams to design innovative learning experiences and measure model efficacy. Key responsibilities include improving pronunciation feedback systems, creating cross-language ASR performance metrics, expanding to new languages, and building robust data infrastructure.

We're looking for someone with extensive experience training large models on GPUs and deploying custom deep learning models. You should be proficient in Python and frameworks like PyTorch, with demonstrated success owning ML pipelines from POC to production. Strong communication skills are essential as you'll need to explain complex ML concepts to non-technical stakeholders.

The company has achieved significant milestones - becoming the top grossing education app in South Korea, expanding to 40+ countries, and reaching a $1B valuation with our Series C round backed by Accel, OpenAI, Founders Fund, Y Combinator and others. With offices in San Francisco, Ljubljana, Seoul, and Tokyo, we offer a truly global opportunity to impact millions of language learners worldwide.

This is an exciting time to join as we scale our AI capabilities and expand to new markets. You'll be part of a tight-knit team where individual contributors can significantly influence the company's direction. We value craft, growth, and working with people we admire. The mission is meaningful - helping the 99% of language learners who currently struggle to achieve their goals due to lack of conversation practice.

We're looking for someone who combines technical excellence with product intuition - someone who can think broadly about model quality in the context of user experience. If you're excited about applying cutting-edge ML to help millions learn languages more effectively, we'd love to talk.