Cloud Consultant II, AI/ML: Google Cloud

Role Overview
This is a Professional Services role, meaning you are not building the core Google Cloud Platform (GCP) products, but rather helping strategic enterprise customers implement them. You will act as a hybrid between a Machine Learning Engineer and a Technical Project Manager.

As a Consultant II, you are the "face" of Google engineering for clients. You will guide them from the scoping phase through to the actual deployment of custom AI solutions, ensuring they are using best practices for MLOps and system design.

Key Responsibilities
Advisory & Implementation: Serve as a trusted advisor to client executives and technical leads, managing the delivery of Cloud AI solutions.

Technical Deployment: Design and deploy pipelines using technologies like TensorFlow, Spark ML, and PyTorch.

Project Management: Manage scope, risks, timelines, and stakeholder expectations (navigating ambiguity is key here).

Thought Leadership: Package the lessons learned from client engagements into published assets and methodologies for the broader team.

Travel: Be prepared to travel up to 30% of the time for client engagements.

Qualifications
Experience: 5+ years of experience in project management and delivering technical solutions.

Consulting Chops: Proven experience in technical client service (consulting). You need to be able to explain complex data flows to non-technical stakeholders.

Technical Stack:

Languages: Python or R.

Frameworks: TensorFlow, Spark ML, CNTK, Torch, Caffe, Scikit-Learn.

Concepts: NLP, Pattern Recognition, Recommendation Systems, Dimensionality Reduction.

Systems Design: Ability to architect and explain data analytics pipelines.

Compensation & Benefits
Google's compensation for this level (likely L4 or L5) consists of three parts: Base Salary, Annual Bonus, and Equity (GSUs). The equity portion at Google is significant and often makes up a large percentage of Total Compensation (TC).