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Metro location and popular Data Scientist title increase competition, but Generative AI specialization reduces density.
Generative AI expertise is specialized but applicable across industries, yielding medium background sensitivity.
Mandatory commercial ML experience and specific frameworks (PyTorch, Hugging Face, LLM fine-tuning) make shortlisting strict.
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Design, develop, and deploy advanced Generative AI models including Large Language Models and deep learning architectures.
Collaborate with business and technical teams to translate client requirements into scalable AI solutions for Fortune 500 companies across diverse sectors.
Maintain and enhance proprietary AI products by processing large datasets to train, fine-tune, validate, and iterate on models ensuring high accuracy and efficiency.
Proven commercial experience as a Data Scientist or Machine Learning Engineer with a strong focus on Generative AI.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field; PhD preferred but not mandatory.
Hands-on proficiency with Python, Pandas, NumPy, Scikit-learn, and machine learning frameworks such as PyTorch, TensorFlow, and Hugging Face.
Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and associated machine learning services.
Experienced in implementing state-of-the-art Generative AI techniques including transformers, GANs, and VAEs, with practical LLM development and fine-tuning expertise.
Able to work effectively with cross-functional teams translating complex business problems into AI-driven solutions for large-scale, diverse industry clients.
Proficient in handling, cleansing, and analyzing large datasets to optimize model performance and product enhancement in a commercial AI environment.