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Remote hiring, a popular Python AI title, and broad skill requirements increase applicant competition significantly.
Core ML engineering skills transfer across industries, though product-specific backend ownership raises some domain specificity.
Non-negotiable technical ML and Python skills are required but no explicit years, producing medium strictness.
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Own design, development, and production deployment of scalable backend AI services powering products like PR Genie and PRR Genie.
Ensure system stability and troubleshoot critical issues for backend systems handling 150-200 daily pull requests.
Develop solutions across web platforms and VS Code extension with real-time communication features, demonstrating full feature lifecycle ownership.
Strong proficiency in Python programming and understanding of machine learning fundamentals including deep learning basics.
Experience with ML libraries such as Scikit-learn, Pandas, and NumPy, and version control using Git.
Work Experience Required: Not explicitly mentioned in the JD.
Mandatory ownership of backend development and model evaluation including hyperparameter tuning.
Candidates with hands-on experience building and scaling AI backend services from architecture to production deployment.
Demonstrates deep technical ownership and capability to diagnose and resolve complex production issues quickly.
Experienced in integrating real-time communication features into web and VS Code extension platforms, suitable for enterprise automation environments.