AI Engineer, Advanced Solutions Lab, Google Cloud
Google· enterprise· Internet & Cloud Services· Sep 11, 2026 · 2mo ago
Chicago, IL, USA · Atlanta, GA, USA · Austin, TX, USA
In office
Full-time
Senior
$120K–$176K est.
6+ years exp
Job description
The AI Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and initiatives that shape the future of AI.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
• 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.
• 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.
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).
Application prep
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Keywords to mirror
aimachine learningmljavapython
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