AI/ML - Voice Building Engineer (Russian), Siri Text-to-Speech
Seattle, Washington, United States
Machine Learning and AI
On the Siri Text-to-Speech team, you'll play a part in the next revolution in human-computer interaction by contribute to a product that is redefining mobile computing. You'll build groundbreaking technology for large-scale systems involving: Spoken language, big data, and artificial intelligence. Plus, you'll work alongside the people who created Siri, the intelligent assistant who helps millions of people get things done — just by asking. The Siri Text-to-Speech team is looking for exceptionally skilled and creative Engineers eager to get involved in hands-on work to improve the overall Siri experience.
- Native-level Russian language fluency/proficiency
- Experience in voice building, testing, and tuning pronunciation, normalization and/or other text processing models
- Ability to implement experiments using scripting languages (Python, bash) and tools written in C/C++
- Solid Understanding or experience working with standard ML algorithms and toolkits
- Solid understanding of phonetic notation such as IPA, SAMPA or CMU
- Ability to create, analyze and optimize voice talent recording scripts and other text corpora for areas such as phonetic and prosodic coverage
- 3-5 years experience working in text-to-speech, speech recognition or related fields
The Siri Text-to-Speech team is looking for Voice Building Engineers to take part in building the voice of Siri. You'll develop and fine-tune ML models used in TTS text processing and backend TTS models for Siri voices. You'll also analyze errors and use your high-quality analysis to develop systemic issues on Siri voices in particular locales. Lastly, you'll implement your ideas directly in our TTS engine or tools. Hundreds of millions of users will experience your contributions through more natural and expressive Siri voices on Apple products.
Education & Experience
Master's degree or higher in Computer Science, Computational Linguistics or a related field