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Tier-1 brand, mid-level ML/AI role in metro with broad LLM expectations increases applicant competition.
Requires specialized LLM/MLOps skills plus financial domain knowledge, limiting cross-industry transferability.
Explicit 5-7 years plus mandatory LLM, Bedrock, Cortex, production deployment and MLOps skills make filters strict.
Develop and deploy GenAI/LLM solutions for tasks including content extraction, semantic search, reasoning, and recommendation.
Design and manage prompt-based and Retrieval-Augmented Generation (RAG) systems, including orchestration and multi-step reasoning workflows.
Lead hands-on building and deployment using Amazon Bedrock and Cortex, alongside managing data pipelines and collaborating with engineering for scalable ML/NLP services.
Advanced degree (Masters preferred) in Data Science, Computer Science, Machine Learning, Statistics, or related field or equivalent experience.
5-7 years of applied experience building and deploying ML/NLP solutions in production environments.
Hands-on experience with Amazon Bedrock (or equivalent LLM platform) and Cortex in enterprise settings.
Strong Python skills and familiarity with ML/DL frameworks (PyTorch/TensorFlow) plus experience building APIs and managing data pipelines for structured/unstructured data.
Experienced in managing end-to-end GenAI/LLM projects including prompt engineering, evaluation methodologies, and production deployment in financial services or asset management domain.
Demonstrates strong software engineering discipline including CI/CD, version control, testing and operational readiness for AI solutions.
Able to communicate complex AI concepts and business tradeoffs effectively to technical and non-technical stakeholders and mentor junior team members.