Solutions Architect, Ml Data Engineering, Google

  • Roma
  • Google
Minimum qualifications: - Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. - Experience with data science/ML concepts and theoretical foundations. - Experience with ML domains (e.g., computer vision, NLP, etc.). Preferred qualifications: - Experience with ML tooling, including machine learning services, etc. - Experience working in the business technology market and with sales/marketing teams in cloud computing or related fields. - Understanding of infrastructure automation, continuous integration/deployment, security, networking, and cloud-based delivery models, including hybrid models. - Ability to communicate complex technical concepts to broad audiences in an engaging way. - Proficiency in Python and Python ML frameworks, including TensorFlow, PyTorch, scikit-learn, etc. About the job: As a Solutions Architect, you will use technical knowledge across industries, best practices, and products. You will help decision makers understand and choose the benefits of Google Cloud for their business to help drive growth and success. You will build proof of concepts and example code to help customers implement solutions. Additionally, you will collaborate with customer-facing roles within Google Cloud to help teams within customer organizations understand how to implement solutions running on Google Cloud. Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology - all on the cleanest cloud in the industry. 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. Responsibilities: - Communicate across customer organizations, and become a trusted advisor to decision makers. - Define the business case for solutions, and guide the solution through launch to market by working with other go-to-market teams. - Travel regularly up to 30% in-region for meetings, technical reviews, and onsite delivery activities. - Create PoC's, example code, and content/assets to scale your work. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.