Major Accountabilities:
- Develop and evaluate machine learning models for various AI applications, leveraging techniques such as supervised learning, unsupervised learning, and reinforcement learning.
- Conduct thorough model evaluation and validation, including performance metrics analysis, to ensure accuracy, reliability, and robustness.
- Implement and optimize automated machine learning (AutoML) pipelines and frameworks to streamline model development, training, and deployment processes.
- Utilize AutoML tools and techniques to automate feature engineering, model selection, and hyperparameter tuning for improved efficiency and scalability.
- Utilize cloud computing platforms such as AWS, Azure, or Google Cloud to deploy and scale machine learning models and applications.
- Leverage cloud-based services and resources for data storage, processing, and analysis to support AI/ML workflows and pipelines.
- Implement continuous integration and continuous development (CICD) pipelines and practices to automate model deployment, testing, and monitoring.
- Integrate AI/ML solutions into existing CICD workflows, ensuring seamless integration with software development processes.
- Apply knowledge of automotive product development processes and industry standards to design and develop AI/ML solutions for automotive applications.
- Collaborate with cross-functional teams to understand product requirements, specifications, and constraints, ensuring alignment with automotive development practices.
- Design and conduct A/B tests and experiments to evaluate the effectiveness and impact of AI/ML models and algorithms in real-world scenarios.
- Analyze test results and make data-driven recommendations for model improvements and optimizations based on observed performance metrics.
- Develop and orchestrate ML workflows using Kubeflow Pipelines to automate model training, evaluation, and deployment processes in Kubernetes environments.
- Implement continuous integration and delivery pipelines using Jenkins to automate build, test, and deployment tasks for AI/ML projects.
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