Machine Learning Jobs at Google with Visa Sponsorship
Machine Learning jobs at Google involve building the models and infrastructure that power products used by billions of people worldwide. The company sponsors H-1B visa, H-1B1 visa, and E-3 visas for qualified ML engineers and researchers, and its in-house immigration team is experienced handling sponsorship across all seniority levels.
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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: San Diego, CA, USA; Mountain View, CA, USA.
MINIMUM QUALIFICATIONS
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 10 years of experience with verifying digital logic at RTL using SystemVerilog for ASICs.
- Experience leading a team completing the full functional verification and performance validation cycle of subsystems such as Camera ML/Multimedia/ISP, Display, TPU/GPU, processors, or at the SOC level.
- Experience constructing reusable verification components and environments using UVM.
- Experience with object oriented programming.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience with Camera ISP image processing or other Multimedia IPs such as Display or Video Codec or ML Accelerator verification.
- Experience with System Verilog Assertions (SVA), assertion-based verification, and formal verification.
- Experience working with software teams to define hardware/software interfacing including control/status registers, security, and error handling.
- Experience working with RTL design and integration teams on methodologies that improve team productivity and velocity.
- Experience with Low Power Verification and power management flows.
ABOUT THE JOB
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. In this role, you will lead and manage a global team of Verification Engineers and independently own Verification closure of various Machine Learning (ML) Accelerators and Multimedia IP designs. This includes verification methodology, infrastructure, test-benches, planning, metrics development and convergence of metrics to deliver high quality ISP Designs. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $192000 - $279000 (USD) + 20% bonus target + equity + benefits.
Responsibilities
Learn more about benefits at Google.
- Plan the verification of complex ML and multimedia hardware at IP and Subsystem level and while supporting full chip level integration by fully understanding the design specification and interacting with architecture and design engineers to identify important verification scenarios.
- Create and enhance constrained-random verification environments using System Verilog and UVM.
- Identify and write all types of coverage measures for stimulus and corner-cases, work with design engineers to debug tests to deliver functionally correct design blocks.
- Manage and mentor a global team of design verification engineers, including methodology department, in all aspects of design verification including test plan reviews, coverage analysis, regression/simulation and debug, and schedule planning for quality verification milestones.
- Manage the interface between SoC Design Verification teams and the ML/Multimedia Hardware Design Verification team including required deliverables for all SoC verification milestones.
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: San Diego, CA, USA; Mountain View, CA, USA.
MINIMUM QUALIFICATIONS
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 10 years of experience with verifying digital logic at RTL using SystemVerilog for ASICs.
- Experience leading a team completing the full functional verification and performance validation cycle of subsystems such as Camera ML/Multimedia/ISP, Display, TPU/GPU, processors, or at the SOC level.
- Experience constructing reusable verification components and environments using UVM.
- Experience with object oriented programming.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience with Camera ISP image processing or other Multimedia IPs such as Display or Video Codec or ML Accelerator verification.
- Experience with System Verilog Assertions (SVA), assertion-based verification, and formal verification.
- Experience working with software teams to define hardware/software interfacing including control/status registers, security, and error handling.
- Experience working with RTL design and integration teams on methodologies that improve team productivity and velocity.
- Experience with Low Power Verification and power management flows.
ABOUT THE JOB
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. In this role, you will lead and manage a global team of Verification Engineers and independently own Verification closure of various Machine Learning (ML) Accelerators and Multimedia IP designs. This includes verification methodology, infrastructure, test-benches, planning, metrics development and convergence of metrics to deliver high quality ISP Designs. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $192000 - $279000 (USD) + 20% bonus target + equity + benefits.
Responsibilities
Learn more about benefits at Google.
- Plan the verification of complex ML and multimedia hardware at IP and Subsystem level and while supporting full chip level integration by fully understanding the design specification and interacting with architecture and design engineers to identify important verification scenarios.
- Create and enhance constrained-random verification environments using System Verilog and UVM.
- Identify and write all types of coverage measures for stimulus and corner-cases, work with design engineers to debug tests to deliver functionally correct design blocks.
- Manage and mentor a global team of design verification engineers, including methodology department, in all aspects of design verification including test plan reviews, coverage analysis, regression/simulation and debug, and schedule planning for quality verification milestones.
- Manage the interface between SoC Design Verification teams and the ML/Multimedia Hardware Design Verification team including required deliverables for all SoC verification milestones.
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 Machine Learning Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at Google.
Get Access To All JobsTips for Finding Machine Learning Jobs at Google
Align your portfolio to Google's ML stack
Google publishes research through Google DeepMind and Google Brain. Demonstrating familiarity with JAX, TensorFlow, or TPU-based training in your portfolio signals direct relevance to the teams most likely to sponsor you.
Target roles that specify research or production
Google separates Research Scientist, Software Engineer (ML), and ML Engineer tracks. Each has different sponsorship timelines internally. Applying to the track matching your background reduces the chance of a role reclassification mid-process.
Request cap-exempt status clarity before accepting
If you're transitioning from a university or nonprofit research role, confirm with the recruiter whether Google will file as a cap-exempt petitioner. This affects whether you can start immediately or must wait for the October 1 H-1B activation date.
Gather degree equivalency documentation early
Google's ML roles typically require a master's or PhD in a quantitative field. If your degree is from outside the U.S., obtain a credential evaluation from a NACES-approved evaluator before your offer stage so it's ready when USCIS reviews the petition.
Understand how E-3 and H-1B1 affect your offer timing
Australian and Chilean or Singaporean nationals can use the E-3 or H-1B1 visa pathways, which sit outside the annual H-1B cap and lottery. Google sponsors both, meaning you can potentially start sooner without waiting for an April registration window.
Find open ML roles at Google through Migrate Mate
Migrate Mate filters Google's open Machine Learning jobs by the visa types the company sponsors. Use it to identify current openings where sponsorship is confirmed rather than sifting through listings with no immigration clarity.
Frequently Asked Questions
Does Google sponsor H-1B visas for Machine Learning roles?
Yes, Google sponsors H-1B visas for Machine Learning engineers and researchers. The company has a dedicated in-house immigration team that manages petitions across all seniority levels, from new graduate hires to senior staff. If you receive an offer, Google will initiate the sponsorship process directly. For roles where you're already in H-1B status with another employer, Google can also file an H-1B transfer.
How do I apply for Machine Learning jobs at Google?
Applications go through Google's careers portal at careers.google.com. Search for roles using terms like 'Machine Learning Engineer,' 'Research Scientist,' or 'ML Infrastructure.' Google's process typically involves a recruiter screen, technical phone interviews focused on ML fundamentals and coding, and a virtual onsite covering systems design, ML theory, and behavioral components. Migrate Mate also lists Google's open ML roles filtered by visa sponsorship type, which makes it easier to confirm sponsorship eligibility before applying.
Which visa types does Google commonly sponsor for Machine Learning positions?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for Machine Learning roles. The H-1B is the most common path and requires entry into the annual lottery for cap-subject candidates. H-1B1 is available to Chilean and Singaporean nationals, and the E-3 is available to Australian citizens. Both the H-1B1 and E-3 sit outside the H-1B cap, so they can move faster for eligible candidates.
What qualifications does Google expect for Machine Learning roles?
Most ML roles at Google list a master's or PhD in computer science, statistics, or a related quantitative discipline as a baseline. Practical experience with large-scale model training, familiarity with Google's open-source frameworks like TensorFlow or JAX, and a track record of applied or published research strengthen your candidacy significantly. For USCIS H-1B purposes, Google's positions are structured to meet the specialty occupation standard, but your degree must correspond directly to the ML field the role covers.
How do I think about the timeline from offer to visa approval at Google?
For H-1B cap-subject candidates, the timeline is tied to the annual registration window in March and an October 1 start date if selected. Google files petitions with premium processing in most cases, which brings USCIS adjudication to within 15 business days of receipt. E-3 and H-1B1 visa candidates generally move faster since there's no lottery. Factor in two to four weeks for the Labor Condition Application the employer files with DOL before the USCIS petition can be submitted.