Machine Learning Jobs at Google with Visa Sponsorship
Google's Machine Learning teams build the models and infrastructure powering products used by billions of people worldwide. The company sponsors H-1B, H-1B1, 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: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
- Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
- Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
- Experience in machine learning (ML).
- Experience working in a technology area.
- Experience taking on new material and delivering it to clients and students.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).
ABOUT THE JOB
As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships.
You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.
The Machine Learning Solutions Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and strategic initiatives that shape the future of AI.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $153,000-$222,000 + 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.
Responsibilities
- Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
- Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
- Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
- Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
- Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.
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: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
- Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
- Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
- Experience in machine learning (ML).
- Experience working in a technology area.
- Experience taking on new material and delivering it to clients and students.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).
ABOUT THE JOB
As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships.
You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.
The Machine Learning Solutions Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and strategic initiatives that shape the future of AI.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $153,000-$222,000 + 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.
Responsibilities
- Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
- Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
- Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
- Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
- Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.
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 Jobs at Google Jobs
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.
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.
Machine Learning at Google jobs are hiring across the US. Find yours.
Find Machine Learning at Google JobsFrequently 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, 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 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.
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