Google Strategic Cloud Engineer, Machine Learning and Big Data, Cloud Professional Services in Seoul, South Korea

The Google Cloud Platform team helps customers transform and evolve their business through the use of Google’s global network, web-scale data centers and software infrastructure. As part of an entrepreneurial team in this rapidly growing business, you will help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Strategic Cloud Engineer, you will play a critical role in ensuring that strategic customers have the best experience moving to the Google Cloud ML suite of products. You will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and CloudML Engine. You will work with customers to identify opportunities to transform their business with machine learning, and will travel to customer sites to deploy solutions and deliver workshops designed to educate and empower customers to realize the full potential of Google Cloud. You will have access to Google’s incredible technology to monitor application performance, debug and troubleshoot product code, and address customer and partner needs.

You will combine engineering expertise and strong client facing skills to lead the timely execution of adopting the Google Cloud Platform solutions to the customer’s requirements. You are an active leader in the cloud area, and you strongly believe that you can help any industry build its next generation business software in the cloud.

Google Cloud helps millions of employees and organizations empower their employees, serve their customers, and build what’s next for their business — all with technology built in the cloud. Our products are engineered for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. And our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life.

Responsibilities
  • Deliver state of the art solutions, including sample code. Solve complex technical customer challenges.
  • Act as a trusted technical advisor for our customers, and solve complex Big Data challenges.
  • Identify new product features and feature gaps, provide guidance on existing product issues, and collaborate with Product Managers and engineers to influence the roadmap of Google Cloud Platform.
  • Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, adapting to the levels and expertise of key business and technical stakeholders accordingly.
  • Be a trusted technical advisor to Google’s most strategic customers.
Qualifications

Minimum qualifications:

  • 3 years of experience building machine learning or Data Science solutions.
  • Experience coding in C++, Java or Python.
  • Ability to speak and write in Korean and English fluently and idiomatically.

Preferred qualifications:

  • Experience with core Data Science techniques such as regression, classification or clustering. Experience with deep learning frameworks (such as TensorFlow, Torch, Caffe, Theano, etc.).
  • Experience working with recommendation engines, data pipelines, or distributed machine learning and experience with data analytics and data visualization techniques and software.
  • Relevant experience in software development, professional services, solution engineering, technical consulting; with expertise in architecting and rolling out new technology and solution initiatives
  • 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)
  • Working knowledge of cloud computing including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems and content delivery networks.
  • Strong customer-facing communication and careful listening skills. Proven success in and genuine enthusiasm for working directly with customer technical teams.

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