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Entry-level ML/dev role with popular skills and metro hiring yields moderate competition.
Requires ML, data warehouse, and dev skills—transferable but leans technical domain expertise.
Multiple mandatory technical skills (ML, BigQuery, Django) increase filtering despite junior experience requirement.
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Develop and maintain AI-powered applications and predictive models to enhance technical operations automation.
Engineer high-throughput data pipelines and optimize operational datasets using Google BigQuery, Pandas, and NumPy.
Build backend systems and interactive tools with Python, Django, and basic front-end frameworks integrated with foundational LLMs like Google Gemini.
0-1 years of experience or freshers with relevant academic/project exposure in AI, ML, and software development.
Proficiency in Python programming, Django framework, and API design using Pydantic-based frameworks.
Good knowledge of SQL and experience with Google BigQuery or similar cloud data warehouses.
Strong understanding of machine learning fundamentals using scikit-learn, data manipulation with Pandas and NumPy, and Linux command-line proficiency.
Ambitious early-career candidate seeking to bridge software engineering, data science, and AI automation development.
Capable of rapid prototyping and building tools that integrate advanced AI models and automation workflows.
Comfortable working on full-stack development within a Linux-based technical operations environment involving cloud data services.