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AI Engineer: ML Solutions Architect for Customers
TechDigital Group
5 hours ago
Full-time
On-site
Seattle, Washington, United States
Role:
Design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI
Work with customers to identify opportunities to apply machine learning in their business, deploy solutions and deliver workshops to educate and empower customers .
Work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
Support customer implementation of Google Cloud products through: architecture guidance,best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Responsibilities:
Be a trusted technical advisor to customers and solve complex Machine Learning challenges.
Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations adapting to different levels of key business and technical stakeholders
. Work with Customers, Partners, and Google Product teams to deliver tailored solutions
into production. Coach customers on the practical challenges in Client systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.
Minimum Qualifications: Bachelor degree in Computer Science, Mathematics or a related technical field or equivalent practical experience. Hands-on experience building machine learning solutions. Experience coding in one or more languages such as Python, Scala, Java, Go, or similar with strong competencies in data structures, algorithms, and software design. Experience working with technical customers. Preferred Qualifications: A solid understanding of the auxiliary practical concerns in production Client systems Experience working with recommendation engines, data pipelines, or distributed machine
learning Experience with deep learning frameworks (such as Tensorflow, pyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures,infrastructure components, ETL/ ELT and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). Relevant experience in technical consulting.
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. Work with Customers, Partners, and Google Product teams to deliver tailored solutions
into production. Coach customers on the practical challenges in Client systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.
Minimum Qualifications: Bachelor degree in Computer Science, Mathematics or a related technical field or equivalent practical experience. Hands-on experience building machine learning solutions. Experience coding in one or more languages such as Python, Scala, Java, Go, or similar with strong competencies in data structures, algorithms, and software design. Experience working with technical customers. Preferred Qualifications: A solid understanding of the auxiliary practical concerns in production Client systems Experience working with recommendation engines, data pipelines, or distributed machine
learning Experience with deep learning frameworks (such as Tensorflow, pyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures,infrastructure components, ETL/ ELT and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). Relevant experience in technical consulting.
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