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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, Google Cloud Platform, or Azure
Familiarity with Docker and Kubernetes
Experience designing developer first APIs and SDK usability patterns
Open source contributions or publicly released Python packages
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, Google Cloud Platform, or Azure
Familiarity with Docker and Kubernetes
Experience designing developer first APIs and SDK usability patterns
Open source contributions or publicly released Python packages