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As a Machine Learning Engineer, you'll help deploy and optimise LLM-based Text-to-Speech models that enable advanced voice cloning and natural-sounding speech synthesis. You'll work alongside like-minded researchers and engineers to bring new features to life, focusing on building scalable, production-ready systems that deliver seamless, low-latency voice experiences. You'll be instrumental in shaping the voice of the ConnexAI product used by our worldwide customer base.
Key Responsibilities:
* You will use tools like TensorRT, ONNX, TorchServe, and Triton to optimise and scale models for real-time, production-level deployment.
* You will implement and maintain CI/CD pipelines and deploy models on cloud infrastructure (AWS)
* You will monitor system performance, troubleshoot issues, and improve deployment strategies.
Requirements:
* A degree in Computer Science, Data Science, or a related field.
* 1+ year of deploying large-scale LLMs and/or TTS systems in production.
* Experience using Docker and Kubernetes (desirable)
* Experience with vLLM, TensorRT, ONNX, TorchServe, Triton, or similar tools.
* Python, cloud platforms, and performance optimisation experience
Why Join Us?
At ConnexAI, you will solve complex problems in a fast-growing, innovative industry. You’ll directly impact the performance and scalability of our LLM-based TTS models, helping position us as a market leader. You’ll be part of a collaborative, dynamic team that values your input and growth.
With the support, resources, and tools you need, you’ll continuously evolve as a professional in the Machine Learning space, tackling new problems in the sector and advancing your career.
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Full-time
Job function
* Job function
Research, Information Technology, and Other
* Industries
Software Development, Telecommunications, and Research Services
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