| Machine Learning consultant at Remote, Remote, USA |
| Email: [email protected] |
| From: Farha khan, Tek Inspirations LLC [email protected] Reply to: [email protected] Job Description - LinkedIn Mandatory, Title : Machine Learning consultant Location: remote, working on US Eastern Time Zone. Duration: 6+ months Exp: 12+ years, Banking Industry experience is excellent. 15 years exp is awesome Note: someone with great communication, very sr and banking experience, that will be a winmust be a high caliber consultant with great communication skills This is an exciting opportunity to participate in a multi-year implementation of a new core banking platform for one of the largest banks in the world. Job is fully remote and will be interacting with a distributed team in the US, Europe and Latin America. Requirements Minimum 12+ years of experience; A strong background in Machine Learning, Deep Learning, and natural language processing; Depth in Data Science, Generative AI and Engineering; Proficiency in Python and relevant Machine Learning libraries (e.g., Transformer, TensorFlow, PyTorch); Experience with transformer-based models (e.g., BERT, GPT, T5, Llama); Solid understanding of statistics, linear algebra, and probability theory; Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing; Excellent problem-solving skills and the ability to work independently and collaboratively; Nice to Have: Banking Industry experience; Responsibilities: Collaborate with researchers and data scientists to design sophisticated machine learning models. Implement and fine-tune neural network architectures, including transformer-based models. Optimize model performance, scalability, and efficiency. Conduct experiments to evaluate model performance, robustness, and generalization. Explore novel techniques and approaches to enhance model capabilities. Stay up-to-date with the latest advancements in NLP, deep learning, and AI research. Work with large-scale datasets, preprocess them, and create appropriate data representations. Select relevant features and ensure data quality for training and evaluation. Collaborate with cross-functional teams, including researchers, software engineers, and product managers. Communicate technical findings and insights effectively. Deploy trained models in production environments. Monitor model performance, troubleshoot issues, and iterate on improvements. Keywords: artificial intelligence |
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| Fri Mar 08 21:00:00 UTC 2024 |