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Tier-1 employer and mid-level ML/LLM role increases applicant density despite niche production-LLM requirements.
Core ML, NLP, and LLM production skills are highly transferable across industries.
Multiple explicit years plus mandatory NLP/LLM, cloud, and production experience create strict shortlisting filters.
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Design and implement AI/ML architectures integrating diverse data sources (pdfs, excels, APIs) for multiple models including ML, GenAI, and LLMs to serve various business use cases.
Identify and develop AI/ML solutions specifically within Sales and Digital domains to enhance user experience, automate processes, and conduct predictive and competitive analysis.
Collaborate cross-functionally to deploy AI/ML models, conduct data analysis to drive decisions, and maintain up-to-date knowledge of AI/ML advancements.
5+ years experience in Python with data science libraries like scikit-learn and Databricks.
3+ years production experience applying NLP techniques including transformers and GPT with large datasets.
2+ years experience applying LLMs (RAG, vector databases, embeddings) to real-world problems.
Experience with cloud platforms (preferably Azure); building APIs; and applying various data science techniques (supervised, unsupervised learning, NLP, time-series forecasting).
Proven ability to apply advanced NLP and LLM techniques in production environments for commercial applications.
Experience architecting AI solutions that integrate multiple data types and AI models effectively to support varied business functions.
Capable of independently driving AI/ML solution development from concept to deployment with strong analytical and communication skills.