Machine Learning Solutions Engineer, Google Cloud Learning Services

3 Months ago • 5 Years + • Artificial Intelligence

Job Summary

Job Description

As a Machine Learning Solutions Engineer, you'll deliver, create, and maintain ML and Generative AI content for ASL participants. You'll work directly with customers, applying ML to their business needs and leading the daily ASL experience. Responsibilities include curriculum enhancements, engaging Google ML experts, recommending models/frameworks, and collaborating within the wider Google ML community. You'll also support customer ML projects, design AI/ML curriculum, stay updated on ML developments, and act as an ML Subject Matter Expert within Google Cloud Consulting.
Must have:
  • Bachelor's degree in relevant field
  • 5+ years coding experience (Python, Java, C++)
  • Cloud experience (Google Cloud)
  • ML model building experience (various data types)
  • Deliver excellent content and support customers' ML projects
Good to have:
  • Master's/PhD in relevant field
  • Experience with TensorFlow, Keras, PyTorch, etc.
  • ML training/consulting experience
  • Experience in fast-paced environments
  • Knowledge of data warehousing concepts

Job Details

Minimum qualifications:

  • Bachelor’s degree in Computer Science, Mathematics, Machine Learning, or equivalent practical experience.
  • 5 years of coding experience in one or more general purpose languages (e.g., python, Java, or C++).
  • Experience working in a cloud environment (e.g., Google Cloud).
  • Experience building ML models for different use cases such as tabular data, images, video, speech, or unstructured text.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, Mathematics, or other quantitative fields.
  • Experience building production ML models with TensorFlow, Keras, Pytorch, JAX, Spark ML, or Scikit Learn.
  • Experience conducting Data and ML technical training or client-facing technical consulting role.
  • Experience working in a fast-moving technology area, while being comfortable working in a dynamic and sometimes ambiguous environment
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).

About the job

As a Machine Learning Solutions Engineer, you will be focused on delivering, creating, and maintaining Machine Learning and Generative AI content for ASL participants. You will be working side by side with our customers, helping them apply Machine Learning to their specific business use cases. You will be leading the day-to-day experience for participants of the Advanced Solutions Lab. Therefore you will always be working to improve the offering, including recommendations on curriculum enhancements, identifying and engaging Google ML experts to support various sessions in the program, or making recommendations on open-sourced models, frameworks, and toolkits for inclusion.

In addition to your work in the Advanced Solutions Lab (ASL), you will also be a member of the wider Google machine learning community. This means that you will have the opportunity to collaborate with other machine learning experts from across Google, work on research and engineering projects, or on customer engagements that deliver real impact on the world.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

  • Own the success of each ML Advanced Solutions Lab experience by delivering excellent content, identifying ML experts across Google to support specific sessions and providing ongoing curriculum enhancements.
  • Lead and support customers' Machine Learning projects from project framing to implementation in the Advanced Solutions Lab.
  • Design AI/ML curriculum by understanding market and customers’ needs, and develop materials collaborating with the team and AI/ML experts across Google.
  • Stay abreast of developments in ML and network across the Google Cloud ML research community, to provide ASL participants with up to date knowledge and unique opportunities for highly interactive engagements with other Google ML experts.
  • Act as an ML Subject Matter Expert within the Google Cloud Consulting team and support other ML activities as they arise.

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