Applied ML Engineer, LLM
Job Description
Speak is revolutionizing language learning through AI-powered tutoring, serving over 40 countries with offices in San Francisco, Ljubljana, Seoul, and Tokyo. As an Applied ML Engineer focusing on LLMs, you'll be at the forefront of developing innovative language learning solutions.
Your role involves the entire ML lifecycle, from ideation to deployment, creating novel LLM product experiences. You'll work on building a Knowledge Graph for tracking learner progress, developing dynamically-generated personalized lessons, and enhancing AI-powered features.
The company has secured over $150M in venture funding from prestigious investors including OpenAI, Accel, Founders Fund, and Khosla Ventures. Since its 2019 launch in South Korea, Speak has become the #1 language learning app there and now serves learners across 15+ languages.
This is an exciting opportunity to join during a period of rapid growth following their Series C funding. The role offers the chance to make a significant impact on the company's direction while working with a tight-knit, talented team. You'll be part of a mission to help millions achieve their language learning goals through innovative AI solutions.
The position offers competitive compensation ($170K-$280K plus equity) and the opportunity to work with a global team. Speak values diversity and maintains a collaborative culture focused on continuous learning and growth. The hybrid work arrangement in San Francisco provides flexibility while maintaining team connectivity.
Responsibilities For Applied ML Engineer, LLM
- Collaborating with the Content team to build out a Knowledge Graph to measure and track learner progress
- Building new types of dynamically-generated personalized lessons
- Working closely with the Product team to enhance AI-powered lessons and learning features
- Improving the assessment and monitoring of prompts via synthetic evaluators
Requirements For Applied ML Engineer, LLM
- 3+ years experience as a machine learning engineer shipping ML systems into production
- Proficiency in Python
- Experience working with LLMs and strong LLM intuition
- Experience building and shipping complex LLM systems into production
- Strong understanding of improving performance & output quality of LLM systems
- Strong product interest and sense
Benefits For Applied ML Engineer, LLM
- Equity
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