| Data Scientist with generative AI - New York. NY onsite (Max rate: $55hr on C2C) at New York, New York, USA |
| Email: [email protected] |
| From: KIRAN, Softcom Systems, Inc [email protected] Reply to: [email protected] Hi, Hope you are doing good. This is Kiran from Softcom System, We have below urgent requirements. Please find the below JD and share your interest, Role: Data Scientist with generative AI Location: New York. NY onsite Duration: 12+ Months Max rate: $55hr on C2C Job Details: Must Have Skills Designing, developing, and implementing cuttingedge generative AI models and algorithms Practical knowledge of Natural Language Processing (NLP) andor Neural network implementation. Proficiency with Python and ML libraries. Nice to have skills generative AI models and algorithms Natural Language Processing (NLP) and Python Detailed Job Description Experienced professional with 6 to 10 years of experience in designing, developing, and implementing cutting-edge generative AI models and algorithms Practical knowledge of Natural Language Processing (NLP) and/or Neural network implementation. Proficiency with Python and ML libraries. Good experience on Model Development and Training Good experience on Prompt engineering technics to write effctive propts Utilize advanced machine learning techniques to develop and train generative AI models Collaborate with cross-functional teams to groom and preprocess large datasets for model training. Algorithm Research and Implementation Proficiency in programming languages such as Python, especially AI-centric libraries like TensorFlow, PyTorch, and Keras. Expertise in generative models like GANs and VAEs. Knowledge of NLP techniques for text generation. Understanding of data pre-processing, augmentation, and synthetic data generation. Good written and verbal communication skills Experience working in an Agile environment. Ability and attitude to learn new things and work in dynamic environments. Keywords: artificial intelligence machine learning New York |
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| Thu Mar 07 00:25:00 UTC 2024 |