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Minimum qualifications:
Bachelor’s degree in computer science, engineering, a related technical field or equivalent practical experience.
10 years of experience in building software products or technical solutions.
3 years of experience with ML/AI algorithms and tools, deep learning or natural language processing; experience designing and implementing systems.
Experience in a customer-facing role.

Preferred qualifications:
Master's degree in computer science or engineering field.
Experience in systems design with ability to architect and explain data analytics pipelines and data flows.
Experience in Python and applied machine learning techniques (i.e., dimensionality reduction strategies, classification, and natural language processing frameworks).
Experience with Applied ML and partnering with cross-functional experts to understand and apply the latest techniques to solve business problems.
Knowledge about Generative AI; experience designing and deploying with one or more from the following technologies: TensorFlow, Spark ML, CNTK, Torch, Caffe, Scikit-learn.
Active TS security clearance.
About the job
The Google Cloud Platform team helps customers transform 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. 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. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an AI/ML Solutions Engineer, you will work on developing reusable solutions by integrating one or more Google Cloud Platform (GCP) products and technologies to solve a recurring business problem in a differentiated, repeatable manner that accelerates time-to-value and reduces risk for customers. You will help develop repeatable assets that reduce implementation friction, and increase maintainability for critical customer problems and use cases, helping them transform their businesses using GCP AI/ML stack and related technologies. You will help customers to develop, deploy, and manage custom solutions in production using Google Cloud technologies.

You will also work with key Google partners and customers to scope engagements, provide solution implementation services, and provide technical guidance and best practice expertise.

Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.

The US base salary range for this full-time position is $167,000-$256,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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 Google.

Responsibilities
Work with cross-functional teams from Customer Engineering, Professional Services, Product, Engineering, Sales and Business Development Managers to develop deployable code, ML models, prescriptive architectural guidance, and  implementation guides.
Serve as a trusted technical advisor to customers and solve recurring mission use cases using GCP services.
Develop integration strategies, enterprise architectures, machine learning models, and application infrastructure required to successfully implement a complete solution using best practices on Google Cloud. 
Work with internal specialists, product and engineering teams to package best practices and lessons learned into thought leadership, methodologies and published assets.
Propose solution architectures and support the deployment of cloud based machine learning solutions according to complex customer requirements and implementation best practices.

AI/ML Solutions Engineer, Public Sector

Jordan Zhu
linkedin.com/in/jordanzhu
Work Experience
Solutions Architect
Stripe
Jun 2021 - Nov 2022
Lead Solutions Architect for Startup segment, partnering cross-functionally with Account Executives and Implementation Consultants to help acquire and deploy prospective high value users on Stripe (including Payments, Billing, Connect, Issuing, etc)
Impacted ~160 deals in a 12 month span, resulting in ~$3M in projected recurring yearly profit (highest staffed SA in segment)
Technical and subject matter expert on Stripe's product suite and customer personas -- crafted custom proof-of-concept prototypes, answered integration questions, and debugged API-related issues to allow users to competitively evaluate Stripe's GTM bundles
Led multiple internal projects focused on knowledge sharing (including cross-organization training on Stripe's Banking-as-a-Solution products), best practices, and scaling SA org impact
Software Engineer
Amazon
Mar 2019 - Apr 2021
Tech lead for rule processor: built UI for marketers to select customizable rules and backend to process rules in AWS EMR. Ingest and filter against millions of records daily, and output result to marketers. Sped up system by 6x.
Technical lead for project to enable marketers to send daily intelligent, machine-learning driven insights to Amazon advertisers.
Led re-architecture of existing system into a more scalable approach, involving multiple designs and spanning months. Built system capable of ingesting millions of records.
Led initiative to improve operational excellence: enabled full end-to-end testing of internal tool and added a system health check that alarmed engineers when a code deployment would cause failures. Decreased CPU usage of internal service from 90% to 10%.
Participated in monthly, 24/7 one week on-call rotation. Engage with customers to discover and debug issues, and discuss with product managers to add feature requests to roadmap.
Led investigation into major system failures and presented two 6-page reports to leadership. Fixed all bugs documented in report.
Software Engineer, Intern
Amazon
2017 - 2018
Developed complete internal dashboard for advertiser metrics, built API endpoints to calculate metrics stored in Elastic Search
Tracked expiring EC2 instances using DynamoDB, created notification service for terminating instances using SQS
Education
B.S.E. in Computer Science
University of Michigan
Sep 2014 - Dec 2018
Skills
AWSPythonC++JavaSQLReactNode.jsJavascriptHTMLCSSRuby

Subject: AI/ML Solutions Engineer Application - Jordan Zhu

Dear Hiring Manager,

I am writing to express my interest in the position of AI/ML Solutions Engineer, Public Sector at Google. With my extensive experience in building software products and deep knowledge of machine learning and artificial intelligence, I believe I am an ideal candidate for this role.

As outlined in the job description, I hold a Bachelor's degree in Computer Science and have over 10 years of experience in building software products and technical solutions. Throughout my career, I have gained valuable customer-facing experience, which has enabled me to understand and address the needs of clients effectively. Moreover, I have 3 years of hands-on experience with ML/AI algorithms and tools, deep learning, and natural language processing, showcasing my ability to design and implement complex systems.

What sets me apart from other candidates is my expertise in systems design and my ability to architect and explain data analytics pipelines and data flows. I have a proven track record of developing and deploying custom solutions using Google Cloud technologies, allowing businesses to transform and optimize their operations. My proficiency in Python and applied machine learning techniques, including dimensionality reduction strategies and natural language processing frameworks, will undoubtedly contribute to the success of the AI/ML Solutions team at Google.

Furthermore, I possess knowledge about Generative AI and have experience working with technologies such as TensorFlow, Spark ML, CNTK, Torch, Caffe, and Scikit-learn. My ability to leverage these technologies to design and deploy innovative solutions will undoubtedly align with Google's mission to develop cutting-edge AI/ML technologies.

Having reviewed the job description, I am confident that my skill set and experience make me an excellent fit for the AI/ML Solutions Engineer role at Google. I am particularly excited about the opportunity to work on developing reusable solutions, providing technical guidance, and serving as a trusted advisor to customers. Additionally, my ability to collaborate across teams and build strong partnerships will contribute to the success of Google's Public Sector initiatives.

Thank you for considering my application. I would welcome the opportunity to further discuss how my expertise aligns with the goals of Google Cloud Platform. I have attached my resume for your reference and look forward to the possibility of an interview. Please feel free to contact me at your convenience.

Sincerely,

[Your Name]