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Mô Tả Công Việc
Design, develop, and implement generative AI models using state-of-the-art techniques. Collaborate with cross-functional teams to define project goals, research requirements, and develop innovative solutions. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Stay up-to-date on the latest advancements in generative AI, deep learning, and related fields, and incorporate new techniques and methods into the team's workflow. Develop and maintain clear and concise documentation of generative AI models, processes, and results. Communicate complex concepts and results to both technical and non-technical stakeholders. Provide support and guidance to other team members, and contribute to a positive, collaborative working environment.
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Yêu Cầu Công Việc
Bachelor's degree in computer science, artificial intelligence, or a related field. 3-5 years of experience in generative AI development. Strong programming skills in Python/Java. Experience with machine learning frameworks, such as TensorFlow, PyTorch, or scikit-learn. Experience with cloud computing platforms, such as Google Cloud Platform (GCP). Excellent communication and problem-solving skills. Ability to work independently and as part of a team.Must Have Technical Skills: ❖ Programming languages: Python ❖ Machine learning frameworks: TensorFlow, PyTorch, or scikit-learn ❖ Cloud computing platforms: Google Cloud Platform (GCP) ❖ Natural language processing (NLP) ❖ Generative adversarial networks (GANs) ❖ Variational autoencoders (VAEs) ❖ Diffusion models ❖ Data visualization
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Hình thức
Full-time
Quyền Lợi
14-months salary package, full salary during probation Sign-on bonus Social insurance based on gross salary MacBook & Monitor provided Lunch & transportation allowances Startup environment: dynamic, collaborative, growth-oriented Leave & holidays: in accordance with state regulations Team building, company trips & regular activities Flexible Working Time: Mon - Fri (9:00 - 18:00; Lunch Break 12:00 - 13:30)
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