Job Details
Responsibilities
- Work with customers on their production Machine Learning deployments to resolve issues and achieve production readiness, availability, and scale.
- Manage issues of Google Cloud customers through effective diagnosis, resolution, documentation, or implementation of investigation tools.
- Develop an in-depth understanding of Google Cloud?s AI/Machine Learning products/solutions and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer issues.
- Understand customer issues, advocate for their needs with internal Product and Engineering teams, to find ways to improve the product, and drive production changes.
- Act as subject matter expert for internal stakeholders in engineering, sales, and customer organizations to resolve technical deployment obstacles to improve Google Cloud, and be part of a team of engineers/consultants that globally ensure 24-hour customer support.
Minimum qualifications:
- Bachelor's degree in the field of Science, Technology, Engineering, Math, or equivalent practical experience.
- Experience reading or debugging code in one of the following: Python, Java, C, C++, Shell, Perl, or JavaScript.
- Experience with Machine Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in advocating for customer needs.
Preferred qualifications:
- 1 year of experience in machine learning, recommendation systems, natural language processing, speech recognition, computer vision, or production deployment of machine learning.
- Experience developing and/or training models using machine learning technologies (e.g., TensorFlow, Keras, PyTorch).
- Experience with exploratory data analysis, model development, and auxiliary practical concerns in production Machine Learning systems.
- Experience with specific machine learning architectures (e.g., AlexNet, LSTM, Conformers, BERT, etc.).
- Effective leadership and influencing skills in the application of AI or Machine Learning, with the ability to lead the design and implementation of AI-based solutions, web services, and debugging tools.