Machine Learning Manager Jobs at Google with Visa Sponsorship
Machine Learning Manager roles 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, H-1B1, and E-3 visas for engineering and ML leadership roles.
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Get Access To All JobsINTRODUCTION
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Our team's mission is to provide end-to-end, fleet-wide scheduling that is efficient, reliable, and easy to use.
As a Tech Lead Manager in the Compute Infrastructure Foundations and Workload Fungibility team, you will lead the engineering efforts that power Alphabet’s ML workloads, supporting critical missions for DeepMind, AdBrain, Search, Waymo, and Cloud.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
ROLE AND RESPONSIBILITIES
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
- Develop the mid-term technical goal and roadmap within the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
- Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
- Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience with infrastructure/ML.
- Understanding of the end-to-end ML development lifecycle.
COMPENSATION
The US base salary range for this full-time position is $207,000-$300,000 + 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.
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
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Our team's mission is to provide end-to-end, fleet-wide scheduling that is efficient, reliable, and easy to use.
As a Tech Lead Manager in the Compute Infrastructure Foundations and Workload Fungibility team, you will lead the engineering efforts that power Alphabet’s ML workloads, supporting critical missions for DeepMind, AdBrain, Search, Waymo, and Cloud.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
ROLE AND RESPONSIBILITIES
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
- Develop the mid-term technical goal and roadmap within the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
- Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
- Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience with infrastructure/ML.
- Understanding of the end-to-end ML development lifecycle.
COMPENSATION
The US base salary range for this full-time position is $207,000-$300,000 + 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.
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 Machine Learning Manager Jobs at Google Jobs
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.
Machine Learning Manager at Google jobs are hiring across the US. Find yours.
Find Machine Learning Manager at Google JobsFrequently 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, 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.
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