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Home›Jobs›Google›Customer Solutions Engineer, AI/ML, Google Cloud (English, Mandarin)
Google

About Google

Empowering the world through technology and information

🏢 Tech👥 100K+📅 Founded 1998📍 Mountain View, California, United States

Key Highlights

  • Over 100,000 employees globally
  • Headquartered in Mountain View, California
  • Parent company Alphabet Inc. valued at $1.5 trillion
  • Google Cloud Platform serves millions of customers

Google LLC, headquartered in Mountain View, California, is a global leader in internet-related services and products, including its flagship search engine, Google Search, and the Android operating system. With over 100,000 employees, Google also offers cloud computing services through Google Cloud P...

🎁 Benefits

Google offers competitive salaries, equity options, generous PTO policies, comprehensive health benefits, and a remote work policy that allows flexibi...

🌟 Culture

Google is known for its engineering-first culture, emphasizing innovation and collaboration. The company fosters a unique environment that encourages ...

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Google

Customer Solutions Engineer, AI/ML, Google Cloud (English, Mandarin)

Google • Singapore

Posted 1w ago🏛️ On-SiteSeniorSolutions engineer📍 Singapore
Apply Now →

Skills & Technologies

PythonJavaC++TensorFlowPyTorchXgboostApache beamHadoopSparkEtl

Job Description

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 6 years of experience in building machine learning solutions and working with technical customers.
  • Experience with coding in general purpose languages (e.g., Python, Java, C++) including data structures and algorithms, and designing cloud enterprise solutions, and supporting customer projects to completion.
  • Experience in testing, maintaining, or launching software products, including software design and architecture.
  • Ability to communicate in English and Mandarin to support client relationship management in this region.
  • Ability to work non-standard hours, including working weekends, night shifts, holidays as required.

Preferred qualifications:

  • Experience in working with recommendation engines, data pipelines, or distributed machine learning.
  • Experience with deep learning frameworks (e.g., Tensorflow, pyTorch, XGBoost).
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, Extract, Transform, and Load/Extract, Load and Transform (ETL/ ELT) and investigative tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
  • Knowledge of the auxiliary queries in machine learning systems.

In this role, you will provide technical guidance to customers adopting Google Cloud Platform (GCP) services. You will be providing best practices on secure foundational cloud implementations, automated provisioning of infrastructure and applications, cloud-ready application architectures, etc. You will provide prescriptive guidance in ensuring that customers receive the quality experience in migrating, building, modernizing, and maintaining applications in GCP. You will work with Product Management and Product Engineering to drive excellence in Google Cloud products and features. You will be a part of a global team that provides support to help customers make the switch to Google Cloud. You will troubleshoot technical problems for customers with a mix of debugging, networking, system administration, updating documentation and coding/scripting. You will make the products easier to adopt and use by making improvements to the product, tools, processes and documentation.

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.

  • Coach customers on tests in ML systems like feature extraction and definition, data validation, monitoring, and features and models management.
  • Work on Machine Learning (ML) deployments to resolve issues and achieve production readiness, availability and partnering with product and engineering teams to improve products based on customer feedback.
  • Manage customer problems through diagnosis, resolution, documentation, or implementation of investigation tools to increase productivity for customer issues.
  • Triage product or system issues, debug/track/resolve by analyzing issue sources and impact on hardware, network, or service operations and quality, and create best practice recommendations, tutorials, blog articles, and sample code.
  • Participate in rotating on-call schedules including during nights, weekends and holidays to ensure prompt and proper resolution of customer-impacting technical tests, and travel up to 15% in-region for meetings and onsite delivery activities.

Interested in this role?

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