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Proficiency in Python for data manipulation, scripting, prototyping, and familiarity with AI-assisted coding.
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Foundational to advanced experience with machine learning technologies and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
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Exposure to agentic AI frameworks (e.g., LangGraph, OpenAI Agents) and familiarity with agent patterns and their effective applications.
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Solid understanding of AI system development, validation, and evaluation practices.
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Experience with Jupyter notebooks, Anaconda environments, or similar tools for experimentation and workflow management.
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Strong grasp of statistics and data science methods (e.g., regression, hypothesis testing, probability distributions).
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Basic to intermediate knowledge of distributed systems, scalable computing approaches, and containerization (e.g., Docker).
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Exposure to cloud platforms (Azure, AWS) and related AI services such as Azure ML, Azure AI Foundry/OpenAI platform, Azure Cognitive Services, and AI Search.
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Familiarity with web services, microservices, and REST APIs, as well as building and working with data architectures.
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Basic knowledge of BI/visualization tools (e.g., Power BI, Microsoft Fabric).
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Understanding of modern computer vision techniques.
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Product development mindset with the ability to work in fast-paced, agile environments.
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Independent and creative approach to problem-solving with the ability to prioritize effectively and deliver with urgency.
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Strong communication and collaboration skills in global and virtual team settings.