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Senior niche ML role with metro location yields moderate applicant density.
Strong ML/AI specialization transferable across industries but senior domain expertise raises fit sensitivity.
Explicit 8–15 years plus deep ML, NLP, GenAI, and deployment skills set strict filters.
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Own full lifecycle of complex machine learning and AI solutions including design, training, deployment, and optimization to address enterprise-scale business problems across commercial operations, supply chain, and customer experience.
Develop advanced ML models including supervised, unsupervised, deep learning, NLP, and Generative AI techniques using tools like TensorFlow, PyTorch, LangChain, and HuggingFace.
Collaborate with data engineering, product management, and business stakeholders to integrate AI solutions into cloud production environments and provide technical mentorship when needed.
8–15 years of experience with strong hands-on data science and machine learning ownership in enterprise settings.
Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or related field; Master’s degree preferred.
Strong proficiency in Python and SQL; hands-on experience with Pandas, NumPy, Scikit-learn.
Experience with cloud platforms (AWS, GCP, or Azure) and practical knowledge of Generative AI tools such as LangChain, HuggingFace, embeddings, and vector databases like FAISS.
Experienced individual contributor accustomed to independently handling complex end-to-end ML projects in enterprise or industrial domains.
Has worked extensively with large-scale enterprise data and production deployment of ML models on cloud platforms.
Familiar with advanced AI including Generative AI applications and responsible AI practices such as model governance and data quality frameworks.