ML Engineer Jobs at Google with Visa Sponsorship
Google hires ML Engineers across research, applied science, and production infrastructure, sponsoring H-1B, H-1B1, and E-3 visas for qualified candidates. The company has an established immigration program that handles sponsorship in-house, making it one of the more navigable paths for international engineers in this field.
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Get Access To All JobsINTRODUCTION
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team's main focus is developing Machine Learning (ML) models to determine whether a user's search query has commercial intent and should be considered for showing Shopping Ads.
As a part of the Ads Query Understanding team, we also partner with other search ads teams (e.g., Retrieval, Auction, UI teams) on developing/applying query-level ML signals to improve ads revenue and user satisfaction.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
ROLE AND RESPONSIBILITIES
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
MINIMUM QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., Python or C++).
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
- Experience with modern machine learning techniques including deep learning, transformers, and model optimization.
- Experience developing accessible technologies.
COMPENSATION
- The US base salary range for this full-time position is $174,000-$252,000 + 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
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team's main focus is developing Machine Learning (ML) models to determine whether a user's search query has commercial intent and should be considered for showing Shopping Ads.
As a part of the Ads Query Understanding team, we also partner with other search ads teams (e.g., Retrieval, Auction, UI teams) on developing/applying query-level ML signals to improve ads revenue and user satisfaction.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
ROLE AND RESPONSIBILITIES
- Write and test product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
MINIMUM QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., Python or C++).
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science, or a related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
- Experience with modern machine learning techniques including deep learning, transformers, and model optimization.
- Experience developing accessible technologies.
COMPENSATION
- The US base salary range for this full-time position is $174,000-$252,000 + 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 ML Engineer Jobs at Google Jobs
Align your portfolio to Google's ML stack
Google's ML hiring centers on TensorFlow, JAX, and large-scale distributed training. Your portfolio and resume should demonstrate hands-on experience with these frameworks, not just familiarity. Projects showing model optimization at scale get traction here.
Target teams actively publishing ML research
Google Brain, DeepMind, and Google Research publish prolifically. Referencing specific papers from these teams in your application or interview prep signals genuine alignment with the work, which matters more than a polished generic cover letter.
Confirm sponsorship intent during the recruiter screen
Google's recruiters handle sponsorship questions directly. Ask explicitly whether the specific team and role are approved for your visa type. Some research-track roles have different internal approval workflows than product engineering positions.
Use Migrate Mate to find open ML Engineer roles at Google
Not every sponsoring role is easy to surface across general job boards. Migrate Mate filters Google's ML Engineer openings by visa type, so you can identify which positions align with your sponsorship category before applying.
ML Engineer at Google jobs are hiring across the US. Find yours.
Find ML Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for ML Engineers?
Yes, Google sponsors H-1B visas for ML Engineers and has a dedicated immigration team that manages the process in-house. Sponsorship is tied to the specific role and team, so you'll want to confirm with your recruiter that the position you're pursuing is approved for H-1B sponsorship before the offer stage.
Which visa types does Google sponsor for ML Engineer roles?
Google sponsors H-1B, H-1B1, and E-3 visas for ML Engineers. The H-1B is the most common path and applies to most nationalities. H-1B1 is available to citizens of Chile and Singapore, and the E-3 is exclusive to Australian citizens. Each visa has different filing timelines and renewal rules, so the right category depends on your nationality.
How do I apply for ML Engineer jobs at Google?
Applications go through Google's careers portal, but roles fill quickly and aren't always easy to filter by sponsorship eligibility. Migrate Mate aggregates Google's open ML Engineer positions and lets you browse by visa type, so you can identify relevant openings faster. A strong application typically includes a tailored resume, a GitHub portfolio demonstrating ML work, and preparation for Google's technical interview process, which includes coding rounds and ML system design.
What qualifications does Google expect for ML Engineer roles?
Most ML Engineer roles at Google require a bachelor's degree at minimum in computer science, electrical engineering, or a closely related field, with a master's or PhD common for research-oriented positions. Practically, Google's hiring bar emphasizes hands-on experience with large-scale ML systems, proficiency in Python and at least one deep learning framework, and the ability to work across research and production environments.
How do I time my job search around the H-1B filing process at Google?
USCIS opens H-1B registration each March for a cap-subject petition, with employment starting October 1 at the earliest. If you're on F-1 OPT, you can start before October 1 using the cap-gap provision. Google typically begins sponsorship paperwork after an offer is signed, so securing your offer before March gives the immigration team enough time to file during that registration window.
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