Data Engineer, Machine Learning, Google Customer Solutions

Google • Mountain View, CA

4h • $124,000 - $178,000

About The Position

As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships.

You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.

Our team is responsible for creating technical solutions to support and maximize traction with Google's advertisers. We lead the design, planning and operations of business growth programs that drive a scalable and investigative programmatic approach to generating incremental business growth, in collaboration with cross-functional teams across Sales, Marketing, Product and Engineering.

The primary focus of this role is to support Data Scientists productionalize models and pipelines that support critical Google Customer Solutions (GCS) business, including resource planning, and maintenance.

You will work on AI based implementations using technologies across Google for various GCS Sales use cases in both a prototyping, and a productionalizing capacity

Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you’ll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.

The US base salary range for this full-time position is $124,000-$178,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at G [https://careers.google.com/benefits/]

Requirements

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 3 years of experience working on data and creating reports, and with database query (e.g., SQL) and visualization tools (e.g., Tableau, dashboards).
• Experience with one or more general purpose programming languages (e.g., Python, C/C++, Java).
• Experience with Artificial Intelligence or Machine Learning Pipelines.

Nice To Haves

• Experience with TensorFlow, TFX, TorchX, JAX, PyTorch, YDF, Vertex AI or other ML modeling and pipeline technologies.
• Experience with Big Data or scaled/sharded system design.
• Experience with Apache Beam, or Python and SQL.
• Proficiency in machine learning, data analysis, or data science, working knowledge of ML tasks including data preparation for ML, evaluation and parameter tuning.
• A passion for engineering excellence and ample experience with unit testing, agile project development, and bug and change management systems.
• Ability to manage projects and prioritize tasks.

Responsibilities

• Design, develop, deploy and maintain end-to-end machine learning and data pipelines. Transitioning models from Colab notebook prototypes into production utilizing ML and pipeline best practices.
• Manage data pipeline operations including data center migration, infrastructure migration, resource management, data pipeline configurations, troubleshooting.
• Collaborate with ML Engineers, Researchers, Data Scientists, Data Analysts and Product Managers to design, build, deploy, and maintain robust solutions to critical problems.
• Write and review technical documents, including design, development and collaborative code reviews.
• Monitor and enhance the performance, stability, and operational efficiency of existing tools and services.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level