AI Engineer, Advanced Solutions Lab, Google Cloud

• Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
• Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
• Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
• Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
• Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
• 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
• Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
• Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.

Preferred qualifications:

• Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
• Experience in machine learning (ML).
• Experience working in a technology area.
• Experience taking on new material and delivering it to clients and students.
• 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).

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
• 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
• Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
• Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.