Machine Learning Engineer

pport AI/ML workflows and pipelines. 7. Implement continuous integration and continuous development (CICD) pipelines and practices to automate model deployment, testing, and monitoring. 8. Integrate AI/ML solutions into existing CICD workflows, ensuring seamless integration with software development processes. 9. Apply knowledge of automotive product development processes and industry standards to design and develop AI/ML solutions for automotive applications. 10. Collaborate with cross-functional teams to understand product requirements, specifications, and constraints, ensuring alignment with automotive development practices. 11. Design and conduct A/B tests and experiments to evaluate the effectiveness and impact of AI/ML models and algorithms in real-world scenarios. 12. Analyze test results and make data-driven recommendations for model improvements and optimizations based on observed performance metrics. 13. Develop and orchestrate ML workflows using Kubeflow Pipelines to automate model training, evaluation, and deployment processes in Kubernetes environments. 14. Implement continuous integration and delivery pipelines using Jenkins to automate build, test, and deployment tasks for AI/ML projects.

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