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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INTRODUCTION
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. As a part of the GenAI for Youth, a team within Kids and Families, you will be dedicated to developing the next-generation of scalable, systemically responsible, and high-integrity AI frameworks that power experiences across Google's products. Your mission is to bridge the gap between foundational model research and highly calibrated, age-appropriate production environments. You will build unified infrastructure that solves complex engineering, user classification, and behavioral modeling challenges once for the entire ecosystem. You will operate across multi-site engineering hubs, establish the technical strategy, algorithmic steering frameworks, and automated validation layers necessary to ensure that Google's AI-driven platform surfaces scale with complete structural accuracy, performance safety, and long-term ecosystem health. The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
ROLE AND RESPONSIBILITIES
Learn more about benefits at Google.
- Develop shared algorithmic frameworks and foundational math in core modeling domains, including runtime behavior steering, latent-space pattern detection, optimization loops, and fine-tuning rooted in industry best practices.
- Streamline engineering efforts across global product lines by shifting fragmented, application-specific pipelines into cohesive, highly scalable, and reusable platform layers.
- Architect definitive, automated evaluation methodologies and standardized benchmarking metrics to provide scientifically rigorous validation models, eliminating manual execution overhead.
- Serve as a technical conduit between product, data science, applied engineering groups, machine learning research organizations, and centralized core infrastructure teams.
- Act as a strategic advisory partner to executive engineering leadership on platform maturity, long-term technical debt reduction, and operational capacity across technical workstreams.
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development, system design, or machine learning infrastructure.
- 8 years of experience working with trust and safety, classification problems, large language model (LLM) safety architectures, fraud or risk detection, identity verification, or adversarial machine learning.
PREFERRED QUALIFICATIONS
- Familiarity with industrial-scale data pipelines, internal data orchestration engines, and high-performance compute infrastructure.
- Demonstrated ability to lead by influence and drive technical alignment across sprawling, matrixed engineering groups without direct operational authority.
- Exceptional systems-thinking capabilities, with a documented history of transforming fragmented technical processes into highly reusable, automated platform engines.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
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
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.