Machine Learning Engineer (Agentic AI)
Responsibilities:
Design and productionalize complex multi-agent systems, focusing on agent communication, task decomposition, and state management.
Take full ownership of deploying agentic workflows into high-availability corporate environments, ensuring robust performance and global scalability.
Architect high-performance FastAPI endpoints and collaborate with vendors to "connect the dots" between the AI agent and the front-end UI.
Build and maintain CI/CD pipelines, Docker containers, and monitoring systems on Azure to track agent reasoning and system health.
Optimize data ingestion and memory grounding for agents using FactorDB, SQL, and NoSQL databases to support structured and unstructured data.
Qualifications:
3-5 years in ML/Software Engineering with proven experience deploying AI solutions within a large-scale enterprise or corporate environment.
Hands-on experience building autonomous or semi-autonomous workflows (e.g., LangGraph, CrewAI) and managing real-time AI interactions.
Expert proficiency in FastAPI for building asynchronous back-end services and integrating with third-party vendor tools.
Proficient in Python, Spark, and core data science packages (PyTorch, sklearn, Pandas) for model optimization and data processing.
Strong background in Docker, version control, and debugging distributed systems where multiple AI components interact.
Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.
CONTRACT
mid
4/15/2026
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