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- Tasks: Join us to deploy and optimise cutting-edge Text-to-Speech models in a dynamic team environment.
- Company: ConnexAI is an award-winning platform revolutionising Conversational AI with innovative technology.
- Benefits: Enjoy a collaborative workspace, opportunities for growth, and the chance to work on impactful projects.
- Why this job: Be at the forefront of AI innovation, working on exciting technologies that shape the future of communication.
- Qualifications: MSc or PhD in Computer Science, plus 3-5 years of relevant experience in machine learning.
- Other info: This role is onsite in Manchester, UK, perfect for those looking to make a real impact.
The predicted salary is between 48000 - 72000 £ per year.
Location: Manchester, UK (Onsite)
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.
Join our Team! We are at the forefront of revolutionising Text-to-Speech (TTS) and Speech Synthesis in Conversational AI, and we are looking for a skilled Senior Machine Learning Engineer to join our expanding team.
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.
- 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.
About ConnexAI: ConnexAI is an award-winning Conversational AI platform. Designed by a world-class engineering team, ConnexAI's technology enables organizations to maximize profitability, increase revenue and take productivity to new levels. ConnexAI provides cutting-edge, enterprise-grade AI applications including AI Agent, AI Guru, AI Analytics, ASR, AI Voice, and AI Quality.
Machine Learning Engineer – Text-to-Speech Manchester, UK (Onsite) employer: Connex
Contact Detail:
Connex Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer – Text-to-Speech Manchester, UK (Onsite)
✨Tip Number 1
Familiarise yourself with the latest advancements in Text-to-Speech technology. Understanding the nuances of TTS models and their applications will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the machine learning and AI community, especially those working with TTS systems. Attend relevant meetups or conferences in Manchester to make connections that could lead to valuable insights or referrals.
✨Tip Number 3
Showcase your hands-on experience with deploying and optimising LLMs and transformers. Prepare to discuss specific projects where you've successfully implemented these technologies, as practical examples can set you apart from other candidates.
✨Tip Number 4
Brush up on your knowledge of GPU scaling and inference servers like Triton and TensorRT. Being able to speak confidently about these tools and how they relate to large-scale deployments will highlight your technical expertise.
We think you need these skills to ace Machine Learning Engineer – Text-to-Speech Manchester, UK (Onsite)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in deploying and scaling machine learning solutions, particularly with Text-to-Speech systems. Emphasise your hands-on experience with LLMs, transformers, and GPU scaling.
Craft a Strong Cover Letter: In your cover letter, express your passion for Conversational AI and detail how your background aligns with the responsibilities of the role. Mention specific projects or achievements that demonstrate your expertise in TTS development and machine learning.
Showcase Technical Skills: Clearly list your technical skills related to the job description, such as proficiency in PyTorch, Hugging Face transformers, and experience with inference servers like Triton or TensorRT. This will help you stand out as a qualified candidate.
Highlight Collaborative Experience: Since the role involves collaboration with the TTS team, include examples of past teamwork in your application. Describe how you contributed to projects and worked effectively with others to achieve common goals.
How to prepare for a job interview at Connex
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deploying and optimising machine learning models, particularly LLMs and transformers. Bring examples of past projects where you successfully scaled TTS systems or similar technologies.
✨Understand the Company’s Technology
Familiarise yourself with ConnexAI's products and their approach to Conversational AI. Knowing how their technology works will help you align your answers with their goals and demonstrate your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities, especially regarding GPU utilisation and scaling machine learning pipelines. Practice explaining your thought process clearly and concisely.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, and future challenges in TTS development. This shows your enthusiasm for the role and helps you gauge if the company is the right fit for you.
