Solutions Architect, ML Data Engineering, Google Cloud

Key Skills

Java Programming, Python Programming, SQL, Machine learning techniques, Natural Language Processing (NLP), PyTorch, TensorFlow, Scikit-learn

Job Description

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.).
• Experience building and deploying ML systems, including applications of ML accelerators.

Preferred qualifications:

• Experience with ML tooling, including machine learning services, etc.
• Experience working with technology systems, designing solutions, or developing business applications.
• 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

• Provide subject matter expertise in data science/machine learning concepts and theoretical foundations.
• 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.