AI Solutions Engineer Jobs at Google with Visa Sponsorship
AI Solutions Engineer roles at Google sit at the intersection of machine learning infrastructure and enterprise client work, requiring both deep technical fluency and the ability to translate complex AI systems for business stakeholders. Google has a well-established sponsorship process for engineering functions and actively files for H-1B, H-1B1, and E-3 visas for this role.
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Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
- Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
- Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
- Experience in machine learning (ML).
- Experience working in a technology area.
- Experience taking on new material and delivering it to clients and students.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).
ABOUT THE JOB
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.
The Machine Learning Solutions Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and strategic initiatives that shape the future of AI.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. 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.
The US base salary range for this full-time position is $153,000-$222,000 + 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 Google.
Responsibilities
- Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
- Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
- Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
- Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
- Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.
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.
INTRODUCTION
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
- Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
- Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
- Experience in machine learning (ML).
- Experience working in a technology area.
- Experience taking on new material and delivering it to clients and students.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).
ABOUT THE JOB
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.
The Machine Learning Solutions Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and strategic initiatives that shape the future of AI.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. 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.
The US base salary range for this full-time position is $153,000-$222,000 + 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 Google.
Responsibilities
- Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
- Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
- Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
- Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
- Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.
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.
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Get Access To All JobsTips for Finding AI Solutions Engineer Jobs at Google Jobs
Build a portfolio demonstrating production AI deployments
Google's AI Solutions Engineer interviews assess hands-on experience with large-scale ML systems, not just theoretical knowledge. Document deployments involving model serving, prompt engineering, or API integration that reached real users or generated measurable business outcomes.
Target Google's Professional Services hiring track
AI Solutions Engineer roles at Google sit within Professional Services, not core engineering. Applications routed through that org get evaluated differently than software engineering pipelines, so aligning your resume to client-facing technical delivery signals you understand the distinction.
Confirm E-3 eligibility before negotiating your offer
If you're an Australian citizen, Google sponsors the E-3 visa for this role, which bypasses the H-1B lottery entirely. Raise your nationality early with the recruiter so the Labor Condition Application process starts on the right visa track from day one.
Time your application around Google's H-1B filing calendar
USCIS opens H-1B registration each March for an April 1 start date. Accepting an offer in December through February gives Google enough runway to register you in that cycle without needing costly premium processing to bridge a later start date.
Use Migrate Mate to filter AI Solutions Engineer roles by visa type
Not every Google job posting specifies which visa types the hiring team will support. Browse verified AI Solutions Engineer openings on Migrate Mate filtered by H-1B, H-1B1, or E-3 sponsorship so you apply only to roles with confirmed sponsorship pathways.
Prepare your credentials for DOL specialty occupation scrutiny
The DOL Labor Condition Application for AI Solutions Engineer roles occasionally draws requests for evidence when the degree field doesn't map cleanly to the job title. A transcript showing coursework in machine learning, statistics, or computer science strengthens your specialty occupation case significantly.
AI Solutions Engineer at Google jobs are hiring across the US. Find yours.
Find AI Solutions Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for AI Solutions Engineers?
Yes, Google sponsors H-1B visas for AI Solutions Engineer roles. The process involves Google filing a Labor Condition Application with the DOL, then submitting an H-1B petition to USCIS on your behalf. Because H-1B is subject to an annual lottery, timing your offer and onboarding around USCIS's March registration window is important for planning your start date.
Which visa types does Google commonly use for AI Solutions Engineer roles?
Google files H-1B petitions for the broadest pool of international candidates in this role. Australian citizens can pursue the E-3 visa instead, which skips the lottery and uses the same LCA process but with far less competition for available slots. Singaporean and Chilean nationals holding H-1B1 status are also eligible, and Google has a track record of filing that category for qualified applicants.
What qualifications does Google expect for AI Solutions Engineer roles?
Google typically looks for a bachelor's degree or higher in computer science, electrical engineering, or a closely related technical field. Beyond credentials, the role requires demonstrated experience building or deploying machine learning systems, working with Google Cloud or similar infrastructure, and translating technical capabilities for enterprise clients. Candidates with prior professional services or solutions consulting backgrounds alongside ML experience stand out.
How do I apply for AI Solutions Engineer jobs at Google?
Search for AI Solutions Engineer openings directly on Google's careers site or browse verified sponsorship-confirmed listings on Migrate Mate, which filters roles by visa type so you can identify positions where your visa category is explicitly supported. Once you apply, expect a recruiter screen followed by technical interviews covering ML system design, coding, and a client-facing case study component specific to the Professional Services track.
How do I plan my timeline if I need H-1B sponsorship at Google?
The H-1B cap year runs October 1 through September 30, with USCIS registration opening each March. If you receive an offer outside that window, Google can file with premium processing to get a decision in about 15 business days, but your work authorization still cannot begin before October 1 unless you're changing from another eligible status. Build at least six months of lead time into your job search to avoid gaps.
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