Python Engineer-7

• Design, develop, and maintain Python SDKs that abstract and simplify AI/ML model training, evaluation, and deployment workflows.
• Build SDKs optimized for notebook-based development (Jupyter, Colab, VS Code) with excellent usability and documentation.
• Implement clean, modular, and extensible APIs to support multiple model types and frameworks.
• Package and release SDKs using best practices (versioning, dependency management, backward compatibility).
• Ensure SDKs are production-ready, supporting deployment, inference, monitoring hooks, and configuration management.
• Collaborate closely with Data Scientists, ML Engineers, and MLOps teams to translate requirements into robust SDK features.
• Write comprehensive unit, integration, and contract tests to ensure reliability and stability.
• Create and maintain developer documentation, examples, and notebooks.
• Enforce software engineering best practices: code reviews, CI/CD, linting, and performance optimization.
• Own the end-to-end lifecycle of SDKs-from design and development to release and maintenance.

Generic Managerial Skills: Common Focus Areas:

• Serve as a liaison to coordinate with cross-functional teams and provide regular updates to technology and business stakeholders
• Identify, mitigate and resolve technical issues and project risks
• Ensure project meets specifications and quality standards
• Proficient in Agile methodology and tools - Jira, Confluence etc.
• Critical analytical and problem-solving skills

• 7+ years of professional Python development experience.
• Strong experience building, maintaining and distributing Python libraries or SDKs used by other developers.
• Solid understanding of AI/ML workflows: training, validation, inference, and deployment.
• Hands-on experience with notebooks (Jupyter/Colab) and designing APIs optimized for interactive usage.
• Experience with packaging and releasing Python libraries:
• setuptools, poetry, or pip
• Semantic versioning
• PyPI or internal package registries
• Strong knowledge of software design principles (SOLID, clean architecture).
• Experience with testing frameworks such as pytest.
• Familiarity with CI/CD pipelines and automated releases.
• Excellent communication skills and ability to work cross-functionally.

Preferred / Nice to Have

• Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• MLOps experience: model versioning, feature stores, model registries, and monitoring.
• Experience deploying models to cloud platforms (AWS, GCP, or Azure).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Experience designing developer-first APIs and SDK usability patterns.
• Open-source contributions or publicly available Python packages.