Machine Learning Engineer

Role: Senior Machine Learning Engineer (Text-to-Speech)

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 optimizing 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.
• Strong Python programming skills.
• 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.

Desirable Skills:

• 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.