Develop innovative AI solutions for challenging business problems.
Discover data sources, get access to them, import them, clean them up, and make them "machine learning ready".
Build backend systems that interact with other microservices.
Train and optimize machine learning models.
Engineer machine intelligence systems and infrastructure for real-world production use at scale.
Explore data features and manipulate data with SQL and scripts.
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like Scikit-learn)
Should be able to understand the problem statement and be able to justify the usage of AI/ML as a solution
Be able to quickly prototype and provide results
Be able to understand requirements and fine tune them to provide results for concrete problems
Be able to deploy ML models in azure server.
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