AI Engineer Jobs at Google with Visa Sponsorship
AI Engineer jobs at Google involve building some of the most advanced systems in the world, with engineering teams that 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 visa, H-1B1 visa, and E-3 visa, for qualified candidates in this function.
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INTRODUCTION
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees.
Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Washington D.C., DC, USA; Atlanta, GA, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA.
MINIMUM QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 10 years of experience in AI testing or research, data analytics, data science, or a related field.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in relevant field.
- 5 years of experience in data analysis for AI Testing with experience in SQL or Python.
- Experience building or partnering with engineering teams to build prototypes for AI testing.
- Experience in designing and conducting experiments or quantitative research, preferably in a technology or AI context.
- Experience in AI systems, machine learning, and their potential risks.
- Strong technical competency with a data-driven investigative approach to solve complex tests, including demonstrable proficiency in data manipulation, analysis, and automation using languages like Python and SQL.
ABOUT THE JOB
Novel Testing is a team within Trust and Safety specializing in complex testing, defining protocols and methodologies for assessing risk where best practices do not currently exist. We pioneer and scale testing programs, streamlining the launch of trustworthy, novel AI products. Work spans from designing first-of-their-kind evaluations for Google’s most ambitious product bets—including autonomous agents, personalization, and the latest hardware—to developing new methodologies for assessing novel foundational model capabilities as they emerge. Advancing in AI evaluation is central to this mission. To scale these methods, we partner closely with engineering teams to build the infrastructure and tools required for automated evaluation.
In this role, you will lead the development of novel testing methodologies for emergent AI, designing evaluation frameworks where established standards do not yet exist. You will address complex testing questions with creative experimentation, designing sophisticated prompt strategies and quantitative analyses to identify systemic risks and edge cases in GenAI products. Bridging the gap between theory and execution, you will move quickly to build and prototype testing solutions that incorporate methodological best practices. You will then partner directly with data science and engineering teams to inform the development of novel testing approaches and automated infrastructure, ensuring your insights scale effectively across Google’s ecosystem. This position demands a researcher’s mindset—capable of deep qualitative and quantitative inquiry—paired with the technical agility to translate those findings into scalable, engineering prototypes.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $171000 - $247000 (USD) + 20% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google.
- Drive the methodological frontier of model evaluation. Partner with DeepMind and Data Science, developing novel, data-driven methodologies for structured and unstructured testing of emerging AI products. Move beyond standard benchmarks, designing sophisticated experimental frameworks, uncovering latent model behaviors and capabilities.
- Define testing and safety standards, working with cross-functional colleagues to ensure they are met. Perform analyses and drive insights to develop model-level and product-level safety mitigations.
- Lead and influence cross-functional teams to implement safety initiatives. Advise executive leadership on complex safety issues.
- Represent Google's AI safety efforts in external forums and collaborations, contributing to industry-wide best practices. Mentor analysts, fostering a culture of excellence, acting as a subject matter expert on adversarial techniques.
- Work with sensitive content or situations and may be exposed to graphic, controversial or upsetting topics or content.
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
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.
Target teams that file E-3 or H-1B1
If you're Australian or from Singapore or Chile, Google actively files E-3 and H-1B1 visa petitions, which aren't subject to the annual lottery. Prioritize these visa types in your application conversations to avoid H-1B cap timing constraints entirely.
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.
Frequently 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 visa, 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 visa 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.