Full-Time Principal Data Scientist

• Design system architecture for ML and AI-driven solutions.
• Lead ML system design discussions.
• Architect scalable cloud-native platforms for ML model training, validation, deployment, and monitoring (AWS/GCP/Azure).
• Build reusable components and reference architectures.
• Define best practices in model versioning, CI/CD for ML, testing, and rollback strategies.
• Deploy and manage machine learning & data pipelines in production environments.
• Collaborate with cross-functional Agile teams.
• Develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting, and automated model deployment.

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
• 10+ years of hands-on work experience developing and applying advanced analytics solutions.
• 4 years of experience programming with Python.
• 7 years of experience productionizing, monitoring, and maintaining models
• Strong programming skills in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, or Vertex AI.
• Hands-on experience designing ML systems using cloud platforms like AWS, Azure, or GCP.

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