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Metro location, mid-level experience, and a generalist Data Scientist title increase competition moderately.
Core ML, NLP, and LLM skills are highly transferable across industries despite insurance domain context.
Explicit 4+ years plus mandatory deep learning, NLP, Generative AI, cloud and framework expertise makes filters strict.
Design, fine-tune, train, and deploy large language models to develop Generative AI capabilities enhancing conversational and decision-making systems.
Own end-to-end processes including data collection, model training, and deployment of deep learning models focused on NLP and Generative AI.
Continuously research and implement state-of-the-art techniques in deep learning, NLP, and Generative AI, collaborating with other data scientists and ML engineers to deliver production-ready solutions.
Minimum 4 years of industry experience in deep learning with specialization in NLP and Generative AI.
Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras.
Experience with cloud services (specifically Azure) for training and deployment, and use of Hugging Face's Transformer libraries.
Proficient programming skills in Python (preferred) or R; experience with large dataset processing including pre-processing and normalization.
Experienced AI/ML engineer with proven capability to develop and scale Generative AI systems in production environments.
Strong in designing and optimizing deep learning training pipelines with a practical focus on efficiency and accuracy.
Comfortable working collaboratively in a team including Data Scientists and other engineers to deliver integrated AI-driven solutions at enterprise scale.