Machine Learning Engineer Jobs at Google with Visa Sponsorship
Machine Learning Engineer roles at Google sit at the intersection of research and production scale, covering everything from recommendation systems to large language models. Google has a consistent track record of sponsoring work visas for this function, and the process is handled through their in-house immigration team.
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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.
Accelerated Language for Synthesis is a mid-level synthesis tool bringing velocity and simplicity to hardware design. Accelerated Language for Synthesis has already been used in multiple chip projects inside of Google and continues to grow in customers and capabilities. The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
ROLE AND RESPONSIBILITIES
- Triage product or system issues and debug, track, and resolve them 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 machine learning (ML) areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
- Deliver better hardware and higher velocity for hardware development to Google semiconductor teams.
- Produce improvements to the Accelerated Language for synthesis compiler.
- Work in Google infrastructure (including Vizier, Flume, and others) to use artificial intelligence and machine learning to better search the space of potential hardware.
BASIC QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in 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).
- Experience in compiler construction.
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 SystemVerilog.
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.
Accelerated Language for Synthesis is a mid-level synthesis tool bringing velocity and simplicity to hardware design. Accelerated Language for Synthesis has already been used in multiple chip projects inside of Google and continues to grow in customers and capabilities. The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
ROLE AND RESPONSIBILITIES
- Triage product or system issues and debug, track, and resolve them 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 machine learning (ML) areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
- Deliver better hardware and higher velocity for hardware development to Google semiconductor teams.
- Produce improvements to the Accelerated Language for synthesis compiler.
- Work in Google infrastructure (including Vizier, Flume, and others) to use artificial intelligence and machine learning to better search the space of potential hardware.
BASIC QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in 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).
- Experience in compiler construction.
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 SystemVerilog.
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 Machine Learning Engineer Jobs at Google Jobs
Align your portfolio with Google's ML infrastructure
Google's ML hiring evaluates applied work on large-scale systems, not just academic research. Before applying, build public projects or papers that demonstrate experience with distributed training, model serving, or production ML pipelines at scale.
Time your application around H-1B cap deadlines
If you need H-1B sponsorship, Google submits registrations in March for the April lottery. Secure your offer and complete internal immigration paperwork well before February so the employer-side filing isn't rushed heading into cap season.
Prepare your degree equivalency documentation early
Google's immigration team may request a credential evaluation if your degree is from outside the U.S. For E-3 or H-1B petitions, USCIS reviews whether your field of study directly supports the ML Engineer role, so gather transcripts and an evaluation letter before your offer letter arrives.
Use Migrate Mate to find open ML Engineer roles at Google
Filtering for visa-sponsored roles manually across Google's careers portal is time-consuming. Migrate Mate surfaces Machine Learning Engineer openings at Google filtered by sponsorship type, so you apply only where your visa category is explicitly supported.
Machine Learning Engineer at Google jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for Machine Learning Engineers?
Yes, Google sponsors H-1B visas for Machine Learning Engineers and has done so consistently across its engineering and research divisions. The process is managed through Google's in-house immigration team. If you're subject to the H-1B cap, Google submits registrations in March for the annual lottery, so your offer and internal paperwork need to be finalized well in advance.
How do I apply for Machine Learning Engineer jobs at Google?
Applications go through Google's careers portal at careers.google.com. Search for Machine Learning Engineer roles and filter by location. Google's ML hiring process typically involves a recruiter screen, technical phone interviews covering ML fundamentals and coding, and a virtual or onsite loop with system design and ML-specific components. Tailoring your resume to reflect production ML experience, not just research, improves your chances of clearing the initial screen.
Which visa types does Google commonly sponsor for Machine Learning Engineers?
Google sponsors H-1B, H-1B1, and E-3 visas for Machine Learning Engineers. H-1B is the most common path for candidates from countries not covered by the other categories. H-1B1 is available to Chilean and Singaporean nationals, and E-3 is exclusively for Australian citizens. Each has different annual caps, processing timelines, and renewal rules, so which visa applies depends on your nationality.
What qualifications does Google expect for Machine Learning Engineer roles?
Google's ML Engineer roles typically require a bachelor's degree or higher in computer science, statistics, or a related field, with practical experience in Python, TensorFlow or JAX, and large-scale model training. Research publications or contributions to open-source ML frameworks strengthen an application. For visa purposes, USCIS will assess whether your degree field directly supports the specialty occupation, so a directly relevant degree matters beyond just getting the offer.
How do I find Machine Learning Engineer roles at Google that sponsor my visa type?
Google lists roles across multiple locations and teams, but not every posting makes visa sponsorship eligibility obvious. Migrate Mate aggregates Machine Learning Engineer openings at Google and filters them by visa sponsorship type, so you can identify roles where H-1B, E-3, or H-1B1 sponsorship is supported without manually researching each posting. This saves significant time if you're working against an OPT deadline or grace period.
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