AI ML Engineer Jobs at Google with Visa Sponsorship
AI ML Engineer jobs at Google are built around deep research and applied machine learning at scale, and the company has an established track record of sponsoring work visas for this function. If you're targeting these roles, Google actively files across multiple visa categories to bring in specialized talent.
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Get Access To All JobsMinimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 8 years of experience with one or more general purpose programming languages (e.g., Java, C/C++, or Python).
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of experience with Machine Learning (ML) or quality, working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, and deep model.
- Experience in C++, Dremel/F1, and TensorFlow.
- Experience in Research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
About the job
We are the core team responsible for Search Ads Personalization. Our personalization models and infrastructure permeate through every part of Search Ads - from Ad Retrieval, Ranking, Auction and Creative writing. As a result, our problems are challenging both in depth (understanding nuances of user's needs), and breadth (scale across entire Google Search user base). We work on modeling user preferences and tasks using a myriad of technologies embedding models, language models, as well as building real-time and large scale inference infrastructure.
Personalizing our Ads has proven to be extremely successful, and as a result, it is a key objective of entire Ads organization. Join us to be in the centre of this personalization revolution! Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
The US base salary range for this full-time position is $207,000-$300,000 + 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
- Focus on personalization (P13N) in the Generative AI space (ads on AIM, personalized ads creatives).
- Collaborate across GenAI teams in Ads Quality and GDM to create and execute on a goal/roadmap to ensure that our users feel connected with our GenAI Ads.
- Work on writing ads creatives or ad explanations to account for user tasks and preferences.
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.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 8 years of experience with one or more general purpose programming languages (e.g., Java, C/C++, or Python).
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of experience with Machine Learning (ML) or quality, working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, and deep model.
- Experience in C++, Dremel/F1, and TensorFlow.
- Experience in Research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
About the job
We are the core team responsible for Search Ads Personalization. Our personalization models and infrastructure permeate through every part of Search Ads - from Ad Retrieval, Ranking, Auction and Creative writing. As a result, our problems are challenging both in depth (understanding nuances of user's needs), and breadth (scale across entire Google Search user base). We work on modeling user preferences and tasks using a myriad of technologies embedding models, language models, as well as building real-time and large scale inference infrastructure.
Personalizing our Ads has proven to be extremely successful, and as a result, it is a key objective of entire Ads organization. Join us to be in the centre of this personalization revolution! Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
The US base salary range for this full-time position is $207,000-$300,000 + 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
- Focus on personalization (P13N) in the Generative AI space (ads on AIM, personalized ads creatives).
- Collaborate across GenAI teams in Ads Quality and GDM to create and execute on a goal/roadmap to ensure that our users feel connected with our GenAI Ads.
- Work on writing ads creatives or ad explanations to account for user tasks and preferences.
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 AI ML Engineer Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer Jobs at Google.
Get Access To All JobsTips for Finding AI ML Engineer Jobs at Google
Align your portfolio to Google's research areas
Google's AI ML hiring prioritizes candidates with published work or open-source contributions in areas like large language models, reinforcement learning, or distributed training. Tailor your portfolio to mirror the research threads appearing in Google DeepMind and Google Brain publications.
Distinguish your visa category before interviewing
Australian citizens can pursue the E-3 instead of entering the H-1B lottery, which means year-round availability with no cap risk. Clarify your eligibility before your recruiter screen so Google's immigration team files the right petition from the start.
Prepare your specialty occupation documentation early
USCIS scrutinizes H-1B petitions for AI ML roles when the degree field doesn't directly match the position title. Gather transcripts, course descriptions, and any graduate research records that tie your specific field of study to the role's technical requirements.
Target Google's PhD and research-track pipelines
Many AI ML Engineer offers at Google originate from internship conversions, PhD fellowships, or research residency programs. These pathways often move faster through internal approvals than external applications and put you in front of the teams that drive sponsorship decisions.
Time your offer acceptance around H-1B cap deadlines
The H-1B cap registration window opens in March each year, with an October 1 employment start date if selected. If you receive a Google offer in late spring or summer, work with their immigration counsel to confirm whether a cap-exempt or concurrent filing option applies to your situation.
Use Migrate Mate to find open AI ML roles at sponsors
Filtering for employers with a verified H-1B, H-1B1 visa, or E-3 sponsorship history saves time before you apply. Use Migrate Mate to browse active AI ML Engineer openings at Google and compare sponsorship patterns across visa categories before your first recruiter call.
Frequently Asked Questions
Does Google sponsor H-1B visas for AI ML Engineers?
Yes, Google sponsors H-1B visas for AI ML Engineer roles. The company participates in the annual H-1B cap lottery and also files for cap-exempt situations where eligible. Google works with in-house immigration counsel to manage petitions, so once you receive an offer, their legal team handles the USCIS filing process directly with you.
Which visa types does Google use for AI ML Engineer roles?
Google sponsors H-1B visas for most international AI ML Engineer hires, and Australian citizens can pursue the E-3 visa as an alternative with no lottery requirement. Singaporean and Chilean nationals holding qualifying degrees may be eligible for the H-1B1 visa. The right category depends on your nationality, degree field, and the specific role classification Google assigns to the position.
How do I apply for AI ML Engineer jobs at Google?
Applications go through Google's careers portal, but the most effective path is a referral from someone inside the relevant org, like Google DeepMind or Google Research. Tailor your resume to the specific team's published work, highlight any ML frameworks you've built or contributed to, and use Migrate Mate to identify open AI ML Engineer roles at Google that are actively being filled.
What qualifications does Google expect for AI ML Engineer roles?
Google's AI ML Engineer roles typically require a master's or PhD in computer science, machine learning, statistics, or a closely related field, along with hands-on experience with frameworks like JAX, TensorFlow, or PyTorch. For USCIS H-1B purposes, your degree field needs to connect directly to the position's duties, so interdisciplinary backgrounds should be documented carefully.
How do I understand the H-1B timeline if I get an offer from Google?
If Google extends an offer and you need H-1B sponsorship, the cap registration window runs in March, with selections announced shortly after and petitions filed by June 30 for an October 1 start. Google's immigration team coordinates each step, but knowing that the full process from registration to employment authorization spans roughly six months helps you plan your transition and any bridging status you may need.