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Remote/hybrid mid-level ML role in metros with broad GenAI skillset increases applicant competition.
ML/LLM/NLP skills transfer across industries, but domain-specific data and forecasting needs moderate sensitivity.
Mandatory 4+ years plus many explicit LLM, RAG, time-series, and deployment skill requirements.
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Lead design, development, and deployment of AI solutions using Machine Learning, Generative AI, LLMs, RAG, and NLP across business domains.
Develop and optimize predictive models and AI applications including LLM-powered solutions, RAG pipelines, and NLP tasks for scalability and performance.
Collaborate with cross-functional teams for model productionization on cloud platforms and mentor junior data scientists.
4+ years experience in data science, machine learning, or AI roles.
Bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, or related field.
Strong Python programming skills with experience in ML libraries (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).
Experience with LLMs, GenAI frameworks (LangChain, LlamaIndex), RAG systems, vector search (FAISS, Pinecone), and NLP techniques.
Experienced in building enterprise-grade Generative AI and LLM applications including fine-tuning and prompt engineering.
Familiarity with model deployment and MLOps best practices on cloud platforms (AWS/GCP/Azure).
Comfortable handling business requirements end-to-end including stakeholder communication and mentoring junior staff.