Develop the best education in the world and make it universally available at Duolingo
Requirements
- Master's degree or higher in AI, Machine Learning, Computer Science, or a closely related field
- 5+ years of hands-on experience building ML systems, including experience with speech technologies (ASR/STT, TTS) or NLP/LLM models
- Solid understanding of ML system design, distributed training, inference optimization, and real-time model serving
- Experience building end-to-end speech pipelines, such as automatic speech recognition, speech synthesis, voice activity detection, or audio enhancement
- Experience training or fine-tuning small or efficient LLMs for real-time applications
- Background in deep learning research, including publications or participation in open-source projects
- Familiarity with MLOps tools, model monitoring systems, and large-scale data pipelines
Responsibilities
- Lead and mentor an 8–10 person team of ML engineers and researchers; recruit and develop top talent as the team grows
- Drive the technical roadmap for our AI models, from research prototyping all the way to production deployment
- Oversee end-to-end ML model development, ensuring models meet performance, latency, scalability, and reliability requirements
- Collaborate cross-functionally with product, design, and infrastructure teams to translate product requirements into effective ML solutions
- Establish strong ML engineering practices, including experimentation pipelines, model training workflows, evaluation benchmarks, and deployment standards
- Ensure production excellence by maintaining monitoring systems, establishing metrics, and driving continuous improvements to model quality and user experience
- Promote innovation by encouraging the team to explore new research ideas, technologies, and optimizations relevant to speech, audio, and language models
Other
- 3+ years of experience managing engineering or research teams, including hiring, mentorship, and performance management
- Excellent communication and collaboration skills; ability to work effectively across engineering, research, and product teams
- Demonstrated ability to drive complex technical projects and deliver high-quality results in fast-paced environments
- Prior experience growing teams or operating in a fast-scaling environment
- Ability to work in an in-person leadership role
