Senior Python Developer - AI/ML Model SDKs

Overview:

• Senior Python Developer responsible for designing, building, and releasing high quality Python Model SDKs used by data scientists and ML engineers

• Develop SDKs that support seamless model training, experimentation, validation, and deployment across the AI/ML lifecycle

• Apply deep Python expertise and strong software engineering practices to build developer friendly libraries

• Design, develop, and maintain Python SDKs that simplify AI/ML model training, evaluation, and deployment workflows

• Build SDKs optimized for notebook based development in Jupyter, Colab, and VS Code

• Implement clean, modular, extensible APIs supporting multiple model types and frameworks

• Package and release SDKs using best practices in versioning, dependency management, and backward compatibility

• Ensure SDKs are production ready and support deployment, inference, monitoring hooks, and configuration management

• Collaborate with data scientists, ML engineers, and MLOps teams to translate requirements into SDK features

• Write comprehensive unit, integration, and contract tests

• Create and maintain developer documentation, examples, and notebooks

• Enforce software engineering best standards including code reviews, CI/CD, linting, and performance optimization

• Manage the end to end SDK lifecycle from design through release and maintenance

• 7+ years of professional Python development experience

• Strong experience building, maintaining, and distributing Python libraries or SDKs for developers

• Strong understanding of AI/ML workflows including training, validation, inference, and deployment

• Hands on experience designing APIs optimized for interactive notebook use

• Experience with Python packaging tools including setuptools, poetry, or pip

• Experience with semantic versioning and package distribution via PyPI or internal registries

• Strong knowledge of software design principles including SOLID and clean architecture

• Experience with testing frameworks such as pytest

• Familiarity with CI/CD and automated release processes

• Excellent communication and cross functional collaboration skills

• Experience with ML frameworks such as TensorFlow, PyTorch, Scikit learn, or XGBoost

• MLOps experience including model versioning, feature stores, registries, and monitoring

• Experience deploying models to AWS, GCP, or Azure

• Familiarity with Docker and Kubernetes

• Experience designing developer first APIs and SDK usability patterns

• Open source contributions or publicly released Python packages