Senior AI / ML Engineer
Posted Updated 4
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Summary
Designs and ships enterprise AI applications built on LLMs, RAG pipelines, and agentic patterns, doing production ML engineering in Python/PyTorch on GCP (Vertex AI) and owning the full MLOps lifecycle — packaging, CI/CD, monitoring, drift detection, and cost-optimized serving on Kubernetes.
Job Summary (List Format): - Design and Development: - Design enterprise AI applications using Large Language Models (LLMs), transformer architectures, Retrieval-Augmented Generation (RAG), and agentic AI patterns (e.g., ReAct). - Build AI agents with tool usage, reasoning, memory, and workflow orchestration. - Integrate AI capabilities with enterprise platforms via secure APIs and microservices. - Machine Learning Engineering: - Develop, evaluate, and optimize machine learning and deep learnin…