Google Strategic Cloud Engineer, Big Data and Machine Learning, Google Cloud in Sydney, Australia
Google Technical Services: Professional Services (gPS) is a team of solution-oriented trusted advisors supporting millions of users worldwide. Our consultative services take our deep technical and product expertise and combine it with our powerful understanding of our customer’s needs and goals to solve their biggest business challenges allowing them to grow and get the most out of Google solutions.
As a Cloud Engineer, you will play a critical role in ensuring that strategic customers have the best experience moving to the Google Cloud Machine Learning (ML) suite of products.
You will design and implement ML 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.
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.
- Deliver state of the art ML solutions and solve complex technical customer challenges.
- Act as a trusted technical advisor to strategic customers.
- 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.
- Deliver best practices recommendations, tutorials, blog articles and technical presentations adapting to different levels of key business and technical stakeholders.
- Travel up to 30% of the time.
- BA/BS degree in Computer Science, Mathematics or related technical field, or equivalent practical experience.
- 3 years of experience in building ML or Data Science solutions.
- Experience writing software in one or more languages such as Python, Scala, R or similar.
- Experience in software development, professional services, solution engineering, technical consulting; with expertise in architecting and rolling out new technology and solution initiatives.
- Experience working with recommendation engines, data pipelines, or distributed machine learning and experience with data analytics and data visualization techniques and software.
- Experience with core Data Science techniques such as regression, classification or clustering, and experience with deep learning frameworks (such as TensorFlow, Torch, Caffe, Theano, etc).
- 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).
- Knowledge of cloud computing including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems and content delivery networks.
- Effective customer-facing communication and listening skills, with the ability to collaborate directly with customer technical teams.
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