Machine Learning Engineer

Function: Text-to-Speech

Join our Team!

We are at the forefront of revolutionising Text-to-Speech (TTS) and Speech Synthesis in Conversational AI, and we're looking for a skilled Senior Machine Learning Engineer to join our expanding team.

The Role

As a Senior Machine Learning Engineer, you will be instrumental in deploying state-of-the‑art Text-to‑Speech models. You will be responsible for scaling and optimising TTS systems, ensuring they are production‑ready and capable of running efficiently on large‑scale deployments.

Key Responsibilities:

• Collaborate closely with the TTS team to deploy and scale advanced models in production environments.
• Lead efforts in optimising TTS pipelines for performance and scalability, particularly focusing on GPU utilisation.
• Implement and maintain LLM (Large Language Models) and transformers, ensuring efficient inference on a large scale.
• Integrate and manage LLM‑based inference servers like Triton, TensorRT, or TorchServe to streamline model deployment and scaling.
• Work on deploying complex pipelines in production, ensuring seamless integration with existing systems.

Must‑Have Qualifications:

• MSc or PhD in Computer Science or a related field.
• 3‑5 years of hands‑on experience deploying and scaling machine learning solutions in production.
• Proven experience in deploying and optimising LLMs/transformers in production environments.
• Knowledge of LLM inference servers (e.g., Triton, TensorRT, TorchServe).
• Experience with GPU scaling for large‑scale machine learning models.
• Expertise in deploying complex machine learning pipelines in production environments.
• Proficiency with PyTorch and Hugging Face transformers.
• Experience with neural audio codecs (e.g., Encodec).
• Background in Text‑to‑Speech (TTS) development.
• Experience with advanced techniques such as Residual Vector Quantization (RVQ), Generative Adversarial Networks (GANs), and diffusion models.

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