AI ML Engineer Jobs at Google with Visa Sponsorship
Google builds its AI ML engineering teams 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 JobsNote: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Cambridge, MA, USA; Reston, VA, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 13 years of experience troubleshooting and triaging technical issues (e.g., hardware, software, application, operational, process).
- 10 years of experience with two or more of the following: Web Technologies, Data/Big Data, Systems Administration, Machine Learning, Networking, Kubernetes, Oracle, SAP.
- Experience reading code in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go, JavaScript) or in system design.
PREFERRED QUALIFICATIONS:
- Experience leveraging Google Cloud Vertex AI and Gemini models to build production-grade agentic workflows (e.g., autonomous agents for code-generation, document processing, or complex system orchestration).
- Experience developing software or infrastructure for high-scale distributed systems and machine learning technologies.
- Understanding of model steering, evaluations (LLM Evaluation), and optimization techniques such as prompt caching, advanced function calling, and context window management.
- Proven track record of identifying technical gaps in partner environments and building reusable assets, deployment kits, or "Platform-in-a-Box" solutions that reduce deployment time from months to weeks.
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 developed 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 a Staff Partner Engineer for AI/ML, you will be the technical "tip of the spear" for Google’s AI partnership strategy. You will act as an entrepreneurial architect, responsible for making Gemini Enterprise a reality within our partners' unique environments. You won't just provide support; you will co-build and solve the "impossible" technical hurdles that prevent partners from reaching production at scale. Your work will directly impact how the world's largest organizations adopt Google’s AI ecosystem, accelerating the transition from pilot projects to enterprise-wide production value.
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 $222,000-$309,000 + 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
- Lead deep technical co-innovation with Google Cloud’s most strategic partners to architect and deploy generative AI solutions (e.g., Gemini Enterprise) in high-scale environments.
- Identify and solve architectural bottlenecks that hinder partner deployment velocity, ranging from model steering and API performance to hybrid-cloud integration constraints.
- Productize bespoke integration work into versioned, validated deployment baselines that can be scaled across the global partner ecosystem.
- Act as an entrepreneurial technical lead, guiding partner CTOs and Principal Engineers on the "art of the possible" and long-term AI strategy.
- Collaborate with internal Product and Engineering teams to feed partner requirements back into the development cycle, ensuring Google’s AI tools are enterprise-ready.
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.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Cambridge, MA, USA; Reston, VA, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 13 years of experience troubleshooting and triaging technical issues (e.g., hardware, software, application, operational, process).
- 10 years of experience with two or more of the following: Web Technologies, Data/Big Data, Systems Administration, Machine Learning, Networking, Kubernetes, Oracle, SAP.
- Experience reading code in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go, JavaScript) or in system design.
PREFERRED QUALIFICATIONS:
- Experience leveraging Google Cloud Vertex AI and Gemini models to build production-grade agentic workflows (e.g., autonomous agents for code-generation, document processing, or complex system orchestration).
- Experience developing software or infrastructure for high-scale distributed systems and machine learning technologies.
- Understanding of model steering, evaluations (LLM Evaluation), and optimization techniques such as prompt caching, advanced function calling, and context window management.
- Proven track record of identifying technical gaps in partner environments and building reusable assets, deployment kits, or "Platform-in-a-Box" solutions that reduce deployment time from months to weeks.
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 developed 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 a Staff Partner Engineer for AI/ML, you will be the technical "tip of the spear" for Google’s AI partnership strategy. You will act as an entrepreneurial architect, responsible for making Gemini Enterprise a reality within our partners' unique environments. You won't just provide support; you will co-build and solve the "impossible" technical hurdles that prevent partners from reaching production at scale. Your work will directly impact how the world's largest organizations adopt Google’s AI ecosystem, accelerating the transition from pilot projects to enterprise-wide production value.
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 $222,000-$309,000 + 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
- Lead deep technical co-innovation with Google Cloud’s most strategic partners to architect and deploy generative AI solutions (e.g., Gemini Enterprise) in high-scale environments.
- Identify and solve architectural bottlenecks that hinder partner deployment velocity, ranging from model steering and API performance to hybrid-cloud integration constraints.
- Productize bespoke integration work into versioned, validated deployment baselines that can be scaled across the global partner ecosystem.
- Act as an entrepreneurial technical lead, guiding partner CTOs and Principal Engineers on the "art of the possible" and long-term AI strategy.
- Collaborate with internal Product and Engineering teams to feed partner requirements back into the development cycle, ensuring Google’s AI tools are enterprise-ready.
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 ML Engineer Jobs at Google Jobs
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, 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.
AI ML Engineer at Google jobs are hiring across the US. Find yours.
Find AI ML Engineer at Google JobsFrequently 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 as an alternative with no lottery requirement. Singaporean and Chilean nationals holding qualifying degrees may be eligible for the H-1B1. 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.
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