Machine Learning Engineer

ConnexAI; Manchester; On-site; GBP 90,000 - 140,000; Full time

Job summary

ConnexAI in Manchester, United Kingdom, is seeking a Senior Machine Learning Engineer to deploy state‑of‑the‑art Text‑to‑Speech models and scale TTS systems for production. You will optimise pipelines for GPU performance and ensure reliable inference at scale.

You will work with PyTorch and Hugging Face transformers, integrate LLM inference servers and complex production pipelines, and push the boundaries of neural audio codecs like Encodec.

Qualifications

• MSc or PhD in Computer Science or a related field.
• 3–5 years of hands‑on experience deploying and scaling ML solutions in production.
• Proven experience deploying and optimising LLMs/transformers in production.
• Knowledge of LLM inference servers (e.g., Triton, TensorRT, TorchServe).
• Experience with GPU scaling for large‑scale ML models.
• Expertise in deploying complex ML 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 RVQ, GANs, and diffusion models.

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 and transformer models, ensuring efficient inference at scale.
• Integrate and manage LLM‑based inference servers like Triton, TensorRT, or TorchServe to streamline deployment.
• Work on deploying complex pipelines in production, ensuring seamless integration with existing systems.

Skills

LLM deployment

PyTorch

Hugging Face

GPU scaling

Transformer models

TTS development

Inference optimization

TorchServe/Triton

VPUs/ GPUs optimization

Education

MSc or PhD in Computer Science or related field

Tools

Triton

TensorRT

TorchServe

Job description

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.