Machine Learning Engineer

ConnexAI
Manchester, UK
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Codecs Python (Programming Language) Machine Learning Chatbots Pytorch Large Language Models Generative AI Information Technology HuggingFace Machine Learning Operations Speech Synthesis TensorRT

Job description

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., 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., * 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.

Requirements

  • 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.

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