Machine Learning Manager Jobs at Google with Visa Sponsorship
Machine Learning Manager jobs at Google sit at the intersection of research leadership and product impact, overseeing teams building large-scale ML systems across Search, Ads, Cloud, and DeepMind. Google has a well-established infrastructure for sponsoring H-1B visa, H-1B1 visa, and E-3 visas for engineering and ML leadership roles.
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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 Manager Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Manager Jobs at Google.
Get Access To All JobsTips for Finding Machine Learning Manager Jobs at Google
Frame your ML leadership portfolio strategically
Google's hiring bar for ML Managers emphasizes both technical depth and cross-functional influence. Document shipped models, team growth, and measurable system improvements before applying. Interviewers probe whether you can lead research and drive production impact simultaneously.
Target teams with active LCA filings
Search DOL's OFLC disclosure data for Google LLC LCA filings under job titles like 'Machine Learning Manager' or 'Engineering Manager, ML.' This surfaces which Google product areas are actively hiring sponsored roles right now, not just historically.
Understand Google's internal transfer sponsorship rules
If you receive a return offer after an internship or contractor stint at Google, ask HR explicitly whether your offer package includes H-1B cap-exempt filing or a cap-subject petition. These pathways have different USCIS timelines and filing windows.
Align your visa category to your citizenship early
Australian citizens applying for ML Manager roles should flag E-3 eligibility to Google's immigration team before offer finalization. E-3 processing bypasses the H-1B lottery entirely, which shortens your timeline to U.S. start date by several months.
Use Migrate Mate to filter Google ML roles by sponsorship type
Search Migrate Mate to browse open Machine Learning Manager positions at Google filtered by the visa types they sponsor. This lets you target the specific team and role level where sponsorship is confirmed before you invest time in the interview process.
Prepare for USCIS specialty occupation scrutiny
ML Manager petitions can draw USCIS Requests for Evidence if the role description blurs managerial and individual-contributor duties. Work with Google's immigration counsel to ensure the job description clearly ties a specific bachelor's degree field to the core management function.
Frequently Asked Questions
Does Google sponsor H-1B visas for Machine Learning Managers?
Yes, Google sponsors H-1B visas for Machine Learning Manager roles. Google is a registered H-1B employer and files petitions for engineering leadership positions including ML management. Because the H-1B is subject to an annual cap and lottery, timing your application cycle matters. Google's immigration team coordinates filing windows with USCIS's April 1 start date, so your offer timeline will be built around that calendar.
Which visa types does Google commonly use for Machine Learning Manager roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for Machine Learning Manager positions. H-1B is the most widely used pathway. H-1B1 is available to Chilean and Singaporean nationals without lottery exposure. E-3 applies exclusively to Australian citizens and also bypasses the H-1B lottery, making it a faster path to a U.S. start date for eligible candidates.
What qualifications does Google expect for a Machine Learning Manager role?
Google typically requires a bachelor's degree or higher in Computer Science, Machine Learning, or a closely related field, alongside hands-on experience leading ML teams that have shipped production systems at scale. Interviewers assess both technical depth, specifically model architecture and infrastructure decisions, and leadership scope. Candidates without a directly relevant degree can sometimes substitute equivalent experience, but this requires stronger documentation for the H-1B specialty occupation standard.
How do I apply for Machine Learning Manager jobs at Google?
Applications go through Google's careers portal at careers.google.com, but surfacing the right open roles by team and sponsorship type takes extra research. Migrate Mate lets you browse confirmed Machine Learning Manager openings at Google filtered by visa sponsorship category, so you can identify which specific teams are hiring sponsored candidates before you apply. Once you apply, Google's process typically includes recruiter screen, technical phone interviews, and an onsite or virtual loop.
How do I plan my timeline when pursuing an H-1B sponsored role at Google?
H-1B cap-subject petitions must be filed during the USCIS registration window each March, with employment starting no earlier than October 1. If you're on F-1 OPT, your start date can precede October 1 under your existing work authorization, but Google will still file the H-1B petition to cover you once OPT expires. Factor in at least six months from offer acceptance to confirmed H-1B status, and confirm with Google's immigration team whether premium processing is available for your petition.