TransPerfect is looking to conduct research and development of novel models in STT, NMT, and TTS systems, bringing innovative AI solutions from research to robust, production-grade implementations.
Requirements
- Strong proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).
- Solid understanding of machine learning and deep learning fundamentals.
- Hands-on experience with at least one of: Speech recognition models (e.g., experience with open-source toolkits such as Kaldi, DeepSpeech, or ESPnet, or designing and implementing a custom STT system).
- Hands-on experience with at least one of: Neural Machine Translation with Transformer-based architectures (e.g., proficiency in frameworks like OpenNMT, Fairseq, or MarianNMT, or hands-on experience developing an end-to-end NMT system).
- Hands-on experience with at least one of: Text-to-Speech systems (e.g., familiarity with models like Tacotron, FastSpeech, or WaveGlow, or building a complete TTS pipeline).
- Experience with training, fine-tuning, or adapting large language models such as LLaMA, GPT, Mixtral.
- Familiarity with handling large datasets and conducting rigorous evaluation of models.
Responsibilities
- Conduct research and development of novel models in STT, NMT, and TTS, independently or in collaboration with other team members.
- Build and iterate on research prototypes, conducting experiments and evaluations.
- Transition promising research into robust, production-grade implementations.
- Work with cross-functional teams including product, engineering, and design to bring AI solutions to life.
- Stay up-to-date with the latest research in speech and language AI and adapt state-of-the-art ideas to our needs.
- Complete all other tasks that are deemed appropriate for this role and assigned by the manager/supervisor
Other
- Master’s or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or a related field OR equivalent industry experience in applied AI research.
- Strong software engineering skills, including experience with version control, modular code design, and working with complex codebases.
- Experience deploying ML models to production environments (cloud or on-prem).
- Proficiency in C and .NET (our broader platform is built in .NET technologies).
- Familiarity with Azure, AWS or other cloud platforms.
