Researcher Position
This role offers an exciting opportunity to contribute to cutting-edge AI research and development.
We are seeking a highly skilled Machine Learning Researcher to conduct independent and collaborative research in STT, NMT, and TTS systems.
* You will work under the guidance of our Head of R&D to develop novel models in these domains.
* Key responsibilities include conducting research and development, building prototypes, and transitioning research into production-grade implementations.
* Collaboration with cross-functional teams is essential for bringing innovative AI solutions to life.
You will stay up-to-date with the latest research in speech and language AI and adapt state-of-the-art ideas to meet our needs.
Requirements
* Masters or PhD in Computer Science, Machine Learning, Computational Linguistics, or related field, or equivalent industry experience in applied AI research.
* 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:
o Speech recognition models (e.g. Kaldi, DeepSpeech, ESPnet, or designing custom STT system).
o Neural Machine Translation with Transformer-based architectures (e.g. OpenNMT, Fairseq, MarianNMT, or developing end-to-end NMT system).
o Text-to-Speech systems (e.g. Tacotron, FastSpeech, WaveGlow, or complete TTS pipeline).
o Experience with training, fine-tuning, or adapting large language models like LLaMA, GPT, Mixtral.
* Familiarity with handling large datasets and rigorous model evaluation.
* Strong software engineering skills, including version control, modular code design, and complex codebases.
Prioritised Qualifications
* Deploying ML models to production environments (cloud or on-prem).
* Proficiency in C# and .NET.
* Familiarity with Azure, AWS, or other cloud platforms.
* Basic understanding of front-end technologies for prototyping demo interfaces.
Desired Skills and Experience
* Passionate about AI research and real-world applications.
* Experimentation, learning, and iteration with limited specs or guidance.
* Clear and proactive communication with peers and stakeholders.
* Initiative and ownership, especially when navigating ambiguity.
* Openness to working with unfamiliar tools or domains when needed.