EndereçoAbout Us : WIZ.AI is a pioneering leader in AI-powered conversational solutions, catering to diverse industries. We empower our clients to enhance their customer service, sales, and marketing strategies through our innovative AI Talkbot platform.
Our platform excels in creating natural, engaging customer interactions across various channels and languages. Job Description : We are seeking a skilled and motivated Algorithm Engineer with expertise in Deep Learning and Language Modelling to join our team.
This position offers an exciting opportunity to work on fintech projects, particularly in Text-to-Speech (TTS) and Natural Language Processing (NLP) technologies, where you will have the chance to improve voice generation and language understanding capabilities of our product.
Key Responsibilities : Deep Learning Expertise : Utilize deep learning to enhance our TTS systems. This includes working on projects that involve improving voice generation, understanding linguistic nuances, and applying deep learning models to language processing.
Text Technology Understanding : While this position may require some development, you will be responsible for gaining a deeper understanding of text technology and NLP concepts.
This includes the ability to evaluate and manipulate text data, identify technical terms, and apply deep learning to language and bot models.
Collaborative Teamwork : Work closely with cross-functional teams, especially those focused on specific languages, to collaborate on TTS development.
Provide feedback and support to colleagues working on different languages, ensuring the accuracy of voice generation and addressing pronunciation issues.
Multilingual TTS Development : Initially, focus on native language TTS development (e.G., Spanish), and as you become comfortable with the workflow, expand your expertise to other languages.
Learn how to manipulate audio, train models for different voice characteristics, and deploy said models effectively. Product Enhancement : Continuously explore and implement techniques to enhance our TTS products, ensuring improved audio quality, language recognition, and user experience.
Progress Updates : Regularly communicate progress updates to the team, maintaining transparency and avoiding isolation. Candidate Requirements : Proficiency in PyTorch, TensorFlow, or any other deep learning framework, with a preference for demonstrated experience in project environments.
Application of the chosen framework across diverse domains. Familiarity with a variety of neural network architectures, including CNN, LSTM, Linear, Transformers, ResNet, and BERT.
Good to have (bonus) : Experience in Natural Language Processing (NLP) coupled with deep learning expertise. Ability to develop NLP models catering to various use cases, such as Text Classification, Token Classification, and Question Answering.
Skills in Text-to-Speech (TTS) and Audio deep learning, including the development of TTS models like Tacotron2 and HiFIGAN, as well as ASR models like Conformer and Whisper.
Proficiency in deploying deep learning models, encompassing tasks like containerization using Docker and model conversion (e.
G., ONNX) to optimize inference speed.
