AI Data Engineer Jobs at Google with Visa Sponsorship
AI Data Engineer jobs at Google sit at the intersection of large-scale data infrastructure and machine learning systems, covering pipelines, feature engineering, and model deployment at significant scale. Google has a consistent track record of sponsoring work visas for this function, including H-1B visa, H-1B1 visa, and E-3 visa classifications.
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Get Access To All JobsINTRODUCTION
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.
MINIMUM QUALIFICATIONS:
- Master's degree in Computer Science, Mathematics, Applied Statistics, Machine Learning, or equivalent practical experience.
- 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
PREFERRED QUALIFICATIONS:
- PhD in Computer Science or Engineering, or a related field.
- Experience in driving a project from an experimental idea, proof-of-concept, and a launched product feature.
- Experience in cross-functional collaboration, with engineering and product teams.
- Experience in publications working with technologies.
- Experience with data ontologies with knowledge in graphs.
ABOUT THE JOB
In this role, you will work in close partnership with several Engineering, Product, and Finance teams across Google to develop and deliver machine learning and predictive analytics solutions at scale to our Sales and Marketing stakeholders. You will build recommendation engines and impact measurement tools for Google Customer Solution Sales and Marketing to increase impact and operational effectiveness across the customer journey. You will also build, test, and scale statistical and machine learning models that measure and amplify impact across the entire advertiser journey from acquisition to growth and continuation.
Additionally, you will be responsible for the regular and ad-hoc delivery of business growth incrementality of programs, as well as the design and statistical analysis of pilot results. You will partner with various teams to develop statistical models, customer-level recommendations and automated solutions, consolidating existing Google technologies and building new ones. You will also work with others on the team to harness the power of Google’s data with machine learning to provide insights at scale that drive both long-term strategy and near-term operations for sales and marketing. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $138000 - $198000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build efficient and scalable Machine Learning (ML) models that help small and mid-size businesses to grow their business, leveraging the power of Google solutions.
- Solve real-world problems with the latest research in deep learning, natural language processing, and understanding.
- Work with product teams to understand their objectives, product requirements, constraints, and key metrics.
- Propose, build, evaluate, and debug machine learning models and algorithms.
- Integrate pipelines, models, and predictions into production serving systems.
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: New York, NY, USA; Mountain View, CA, USA.
MINIMUM QUALIFICATIONS:
- Master's degree in Computer Science, Mathematics, Applied Statistics, Machine Learning, or equivalent practical experience.
- 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
PREFERRED QUALIFICATIONS:
- PhD in Computer Science or Engineering, or a related field.
- Experience in driving a project from an experimental idea, proof-of-concept, and a launched product feature.
- Experience in cross-functional collaboration, with engineering and product teams.
- Experience in publications working with technologies.
- Experience with data ontologies with knowledge in graphs.
ABOUT THE JOB
In this role, you will work in close partnership with several Engineering, Product, and Finance teams across Google to develop and deliver machine learning and predictive analytics solutions at scale to our Sales and Marketing stakeholders. You will build recommendation engines and impact measurement tools for Google Customer Solution Sales and Marketing to increase impact and operational effectiveness across the customer journey. You will also build, test, and scale statistical and machine learning models that measure and amplify impact across the entire advertiser journey from acquisition to growth and continuation.
Additionally, you will be responsible for the regular and ad-hoc delivery of business growth incrementality of programs, as well as the design and statistical analysis of pilot results. You will partner with various teams to develop statistical models, customer-level recommendations and automated solutions, consolidating existing Google technologies and building new ones. You will also work with others on the team to harness the power of Google’s data with machine learning to provide insights at scale that drive both long-term strategy and near-term operations for sales and marketing. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $138000 - $198000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build efficient and scalable Machine Learning (ML) models that help small and mid-size businesses to grow their business, leveraging the power of Google solutions.
- Solve real-world problems with the latest research in deep learning, natural language processing, and understanding.
- Work with product teams to understand their objectives, product requirements, constraints, and key metrics.
- Propose, build, evaluate, and debug machine learning models and algorithms.
- Integrate pipelines, models, and predictions into production serving systems.
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.
See all 49+ AI Data Engineer Jobs at Google
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Google
Align your portfolio to Google's stack
Google's AI Data Engineer roles prioritize hands-on experience with distributed systems, BigQuery, Vertex AI, and TensorFlow. Structure your portfolio around end-to-end ML pipelines and large-scale data processing to match what their engineering teams are actively building.
Target roles listed under specific product teams
Google posts AI Data Engineer positions across Google Cloud, DeepMind, and Google Research. Applying to team-specific openings rather than generic postings signals a clearer fit and gets your application to hiring managers closer to the actual work.
Confirm your visa type before the offer stage
Google sponsors H-1B, H-1B1 visa, and E-3 visas. Knowing which classification applies to your nationality before final-round interviews helps you respond clearly when compensation and start-date conversations begin, avoiding delays in the offer process.
Prepare for H-1B cap timing if you're cap-subject
If you need a cap-subject H-1B, USCIS registration opens in March for an October 1 start date. Receiving an offer in Q4 or Q1 means you'll likely wait through a full lottery cycle, so negotiate start dates and interim work authorization options with your recruiter early.
Use Migrate Mate to filter verified AI Data Engineer openings
Identifying which Google roles are actively open to visa sponsorship takes real research. Use Migrate Mate to filter AI Data Engineer jobs at Google by visa type, so you're applying to roles where sponsorship is confirmed rather than assumed.
Request clarity on LCA filing and prevailing wage tier
Google files a Labor Condition Application with the DOL before your H-1B petition can proceed. Ask your recruiter which wage level the role is certified at, since Level I and Level II certifications can affect the offer structure and your petition's approvability.
Frequently Asked Questions
Does Google sponsor H-1B visas for AI Data Engineers?
Yes, Google sponsors H-1B visas for AI Data Engineer roles. They also sponsor H-1B1 visas for Chilean and Singaporean nationals and E-3 visas for Australian nationals. The specific classification depends on your citizenship. Google's legal and HR teams manage the petition process internally, so your recruiter will coordinate the filing once you have a confirmed offer.
Which visa types does Google commonly use for AI Data Engineer roles?
Google uses the H-1B for most international AI Data Engineers, the H-1B1 visa for Chilean and Singaporean nationals, and the E-3 exclusively for Australian citizens. AI Data Engineer roles qualify as specialty occupations under USCIS guidelines because they require at minimum a bachelor's degree in computer science, data engineering, or a closely related field.
How do I apply for AI Data Engineer jobs at Google?
Applications go through Google's careers portal at careers.google.com. Search for AI Data Engineer roles filtered by location and team. The process typically involves an initial recruiter screen, followed by technical phone interviews covering data systems and ML infrastructure, then a virtual on-site loop. You can also browse open, visa-sponsorship-confirmed AI Data Engineer positions at Google through Migrate Mate before applying directly.
What qualifications does Google expect for AI Data Engineer roles?
Google expects a bachelor's or master's degree in computer science, data engineering, or a related technical field. Beyond credentials, strong candidates demonstrate production-level experience with distributed data pipelines, proficiency in Python or SQL, and familiarity with ML workflow tooling. For more senior levels, prior work on feature stores, model serving infrastructure, or real-time data systems is a practical differentiator.
How do I plan my timeline if I need Google to sponsor my visa?
Timeline depends on your visa type. E-3 and H-1B1 visas have no annual cap and can be filed throughout the year, so start dates are more flexible. Cap-subject H-1B petitions require USCIS registration in March, with employment beginning no earlier than October 1. If you're cap-subject, factor in a six-to-twelve month gap between offer and start date, and confirm whether Google offers cap-gap or OPT extension support during that window.