Applied ML Engineer, Speech
Description For Applied ML Engineer, Speech
Speak is revolutionizing language learning through AI technology, having recently achieved a $1B valuation with their Series C funding. As an Applied ML Engineer in the Speech team, you'll be at the forefront of developing cutting-edge speech recognition models that help teach language fluency. The role involves end-to-end ownership of the modeling pipeline, from training and experimentation to deployment and monitoring.
The company has already established itself as the top-grossing education app in South Korea and has expanded to over 40 countries globally. Backed by prestigious investors including Accel, OpenAI, Founders Fund, Y Combinator, and Khosla Ventures, Speak is well-positioned for continued growth. With a team of 90+ members across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana, they're creating an AI-powered experience that replicates natural conversation flow without requiring a human partner.
This role offers a unique opportunity to work on innovative projects including ASR, assessment, pronunciation, and content personalization. You'll collaborate closely with Product teams to design learning experiences and measure the impact of production models on user outcomes. The position requires strong technical expertise in machine learning, particularly in speech recognition, combined with the ability to think strategically about product implementation.
Working at Speak means joining at a pivotal time when individual contributions can significantly impact the company's direction. The culture emphasizes craft, growth, and working with admirable colleagues. The mission is meaningful - helping millions achieve language fluency who otherwise wouldn't have the opportunity. With their recent Series C funding and proven product-market fit, this role offers the chance to be part of a transformative education technology company.
Responsibilities For Applied ML Engineer, Speech
- Training and deploying ASR models end-to-end, including monitoring, performance tracking, and retraining
- Improving the pronunciation model that provides precise feedback
- Creating metrics to measure ASR performance across tasks and languages
- Expanding ASR systems to new languages and markets
- Building and maintaining data infrastructure such as training/evaluation datasets and labeling pipelines
Requirements For Applied ML Engineer, Speech
- Extensive experience training large models on GPUs and deploying custom deep learning models
- Proficiency in Python and common Deep Learning frameworks like PyTorch
- Demonstrated experience owning ML pipelines end to end, from POC to production
- Strong communication skills and ability to explain complex ML concepts to non-technical stakeholders
- Sharp product sense and ability to think broadly about model quality in user experience context
Benefits For Applied ML Engineer, Speech
- Global work environment with offices in San Francisco, Ljubljana, Seoul, and Tokyo
- Opportunity to work with top investors and growing team
- Chance to make significant impact on company direction
- Work with respected team members
- Opportunity for international travel
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