Python Developer

Job Description

Must Have Technical/Functional 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, Google Cloud Platform, 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.

Roles & Responsibilities

•             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