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Tier-1 brand, metro location, mid-level ML role but specialized LLM skills moderate competition.
Role demands specialized ML/LLM, deep learning, and production ML engineering skills, limiting cross-industry transferability.
Requires advanced degree, 6+ years, specific ML/LLM tools, cloud and production-grade engineering.
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Design and deliver AI/ML-driven technology products addressing business problems at JPMorgan Chase scale.
Build and improve AI processing pipelines including LLM integration, agentic workflows, and Retrieval-Augmented Generation (RAG) methods for enhanced accuracy and throughput.
Collaborate with cross-functional teams to develop scalable ML systems and conduct large-scale data modeling experiments for business insights.
Advanced degree in Computer Science, Data Science, or equivalent discipline.
Minimum 6 years of industry experience with at least 4 years as hands-on ML Engineer, Data Engineer, or Data Scientist.
Hands-on expertise with Python, FastAPI, deep learning frameworks, and experience designing scalable distributed ML models in production.
Experience with analytics tools (SQL, Python, AWS suite) and machine learning techniques (regression, classification, clustering, causal inference).
Experience driving end-to-end projects as a Senior Data Scientist or equivalent role preferred.
Proficiency with LLMs, building RAG pipelines, and large-scale machine learning system design.
Familiarity with cloud-based ML pipelines, specifically AWS ecosystem (Sagemaker, etc.) and frameworks like TensorFlow or PyTorch on GPU hardware.