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ConnexAI

Machine Learning Engineer

Manchester
Posted about 22 hours ago
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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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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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.

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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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Skills

Python
Machine Learning Deployment
LLM Optimization
Triton
TensorRT
TorchServe
GPU Scaling
PyTorch
Hugging Face Transformers
Text-to-Speech
Neural Audio Codecs
Residual Vector Quantization
Generative Adversarial Networks
Diffusion Models
Transformers

Location

Manchester, England, United Kingdom

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