AI Engineer Jobs at Google with Visa Sponsorship
Google builds some of the most advanced AI systems in the world, and its engineering teams reflect that ambition. For AI Engineers, roles span model development, infrastructure, and applied research across products used by billions. Google has a well-established process for sponsoring work visas, including H-1B, H-1B1, and E-3, for qualified candidates in this function.
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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 Engineer Jobs at Google Jobs
Align your portfolio to Google's AI research
Google publishes research across DeepMind, Google Brain, and Google Research. Before applying, map your published work, open-source contributions, or projects to these areas. Reviewers in AI hiring look for evidence you've engaged with problems at this scale.
Use Migrate Mate to filter open AI Engineer roles
Sponsor-confirmed AI Engineer positions at Google are searchable on Migrate Mate, filtered by visa type. This cuts out the guesswork of cold-applying to roles where sponsorship eligibility hasn't been verified upfront.
Time your offer around H-1B cap deadlines
If your role requires H-1B sponsorship, Google must register you in the USCIS lottery in March for an October 1 start. Starting your interview process between October and January gives recruiters enough runway to move through rounds before the registration window.
Prepare documentation that supports a specialty occupation finding
USCIS scrutinizes AI Engineer petitions to confirm the role requires a specific degree in a relevant field, not just a general computer science background. Have transcripts, degree equivalency evaluations, and job description documentation ready before your employer files Form I-129.
Clarify internal transfer options if you're already in the U.S.
Google frequently hires through its intern-to-full-time pipeline and internal mobility programs. If you're on OPT, confirm whether your role and start date allow a cap-exempt or change-of-status H-1B filing before your authorized period expires, so there's no gap in work authorization.
AI Engineer at Google jobs are hiring across the US. Find yours.
Find AI Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for AI Engineers?
Yes, Google sponsors H-1B visas for AI Engineer roles. The process involves USCIS lottery registration in March, with employment starting October 1 if selected. Google's legal and immigration teams manage the filing process after an offer is extended, including the Labor Condition Application that must be certified by the DOL before the petition is filed.
Which visa types does Google use for AI Engineer roles?
Google sponsors H-1B, H-1B1, and E-3 visas for AI Engineers depending on your nationality. H-1B1 is available to Singaporean and Chilean nationals, and E-3 is exclusive to Australian citizens. Both H-1B1 and E-3 bypass the annual lottery, which makes them significantly faster pathways to employment for eligible candidates.
What qualifications does Google expect for AI Engineer roles?
Google AI Engineer roles typically require a bachelor's degree at minimum in computer science, machine learning, or a closely related field, with a master's or PhD preferred for research-adjacent positions. Practical experience with large-scale model training, ML infrastructure, or applied AI systems carries significant weight, particularly if supported by publications or verifiable open-source contributions.
How do I apply for AI Engineer jobs at Google?
You can browse and apply for sponsor-confirmed AI Engineer positions at Google through Migrate Mate, which filters roles by visa type so you know upfront whether your visa category is supported. Google's hiring process for AI Engineers typically includes a recruiter screen, technical phone interviews, and a virtual onsite loop covering coding, system design, and ML-specific problem solving.
How do I plan my timeline if I need visa sponsorship at Google?
If you need H-1B sponsorship, target a start date of October 1 and work backward: USCIS registration opens in March, so you'll want an offer in hand by February at the latest. For E-3 or H-1B1 roles, there's no lottery, and consular processing typically takes two to six weeks after your employer receives DOL certification, giving you more scheduling flexibility.
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