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Strong employer brand, metro locations, and popular ML/AI role attract many qualified applicants.
ML/AI skills transfer across industries but enterprise data-integration and delivery experience raise domain specificity.
Many mandatory technical skills (LLMs, TF/PyTorch, cloud, data integration) and delivery expectations increase filter strictness.
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Design, develop, and deploy machine learning and generative AI models addressing business needs, including large language models like GPT-3 or GPT-4.
Work with large-scale datasets using Python, SQL, and AI/ML libraries (Scikit-learn, TensorFlow, PyTorch, Keras, AutoML).
Collaborate with cross-functional teams to translate business requirements into AI-driven solutions and mentor junior team members on AI best practices.
Experience with AI/ML, specifically generative AI and large language models (LLMs).
Proficiency in programming (Python) and working with AI/ML libraries and cloud platforms (Azure, AWS, or GCP).
Bachelor's degree in Business Analytics, Computer Science, Statistics, or Master's in Data Science.
Work Experience Required: Not explicitly mentioned in the JD
Strong technical expertise in AI/ML model development and deployment with experience in generative AI frameworks and LLM fine-tuning.
Able to manage data quality, ensure coding standards, and apply NLP techniques for text understanding and sentiment analysis.
Experienced in collaborating with multidisciplinary teams and leading AI innovation in delivery management roles within data and analytics environments.