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 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.
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