Senior ML Engineer Jobs at Google with Visa Sponsorship
Senior ML Engineer roles at Google sit at the intersection of large-scale infrastructure and applied research, covering production model deployment, ML platform engineering, and deep learning systems. Google has a consistent track record of sponsoring work visas for this function, supporting candidates through H-1B, H-1B1, and E-3 pathways.
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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.
As an AI/Machine Learning Software Engineer in the team, you will play a key role in improving Chrome's agentic capabilities' quality and building Gemini in Chrome features. Additionally, you will be responsible for writing test plans and automated tests, root-causing and fixing bugs, and deploying experiments.
Chrome is dedicated to building a better, more open web. We’re focused on making a better browser (on both desktop and mobile) to help users take advantage of all the web has to offer in a safe and secure way. Chrome is available across all major platforms — iOS, Android, Windows, Mac, Linux and Chrome OS. We also built Chrome as an open source project so the entire web ecosystem could benefit from the latest innovations in speed, simplicity and security.
ROLE AND RESPONSIBILITIES
- Build, tune, and improve ML models for vertical integrations.
- Employ a wide variety of approaches to improve the model such as prompt engineering, agent orchestration and post-training.
- Contribute to creating testing evaluation datasets and autoraters to help us hill-climb and push the frontiers of what Gemini can do in Chrome.
- Run live experiments, deploying models in production, and using experimental results to improve model performance.
- Collaborate with product managers, User Experience (UX) designers, and other engineers to turn requirements into technical solutions.
MINIMUM QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in C++ or Python.
- 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).
- 1 year of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
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 feature engineering and analyzing data for building ML models.
- Experience using ML tools to improve the product.
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.
As an AI/Machine Learning Software Engineer in the team, you will play a key role in improving Chrome's agentic capabilities' quality and building Gemini in Chrome features. Additionally, you will be responsible for writing test plans and automated tests, root-causing and fixing bugs, and deploying experiments.
Chrome is dedicated to building a better, more open web. We’re focused on making a better browser (on both desktop and mobile) to help users take advantage of all the web has to offer in a safe and secure way. Chrome is available across all major platforms — iOS, Android, Windows, Mac, Linux and Chrome OS. We also built Chrome as an open source project so the entire web ecosystem could benefit from the latest innovations in speed, simplicity and security.
ROLE AND RESPONSIBILITIES
- Build, tune, and improve ML models for vertical integrations.
- Employ a wide variety of approaches to improve the model such as prompt engineering, agent orchestration and post-training.
- Contribute to creating testing evaluation datasets and autoraters to help us hill-climb and push the frontiers of what Gemini can do in Chrome.
- Run live experiments, deploying models in production, and using experimental results to improve model performance.
- Collaborate with product managers, User Experience (UX) designers, and other engineers to turn requirements into technical solutions.
MINIMUM QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in C++ or Python.
- 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).
- 1 year of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
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 feature engineering and analyzing data for building ML models.
- Experience using ML tools to improve the product.
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 Senior ML Engineer Jobs at Google Jobs
Tailor your resume to Google's ML stack
Google's Senior ML Engineer interviews heavily test systems design at scale. Frame your experience around distributed training, model serving infrastructure, or ML pipeline tooling rather than generic data science projects. Reviewers are looking for production credibility, not research summaries.
Distinguish yourself in the system design round
Google's technical loop for ML roles includes a dedicated ML systems design interview. Prepare to architect feature stores, training pipelines, and inference systems under latency and throughput constraints. This round often determines leveling, which directly shapes your visa petition's wage tier.
Understand how Google's offer timeline affects H-1B filing
If you're targeting an H-1B, Google typically files in April for an October 1 start. USCIS requires a petitioner-employer relationship before submission, so your offer must be in place before the registration window opens in mid-March.
Search verified sponsorship data before applying
Use Migrate Mate to filter Senior ML Engineer openings at Google by visa type. This helps you confirm active sponsorship for your specific category and focus your applications on roles aligned with your current status.
Request premium processing if your status is time-sensitive
If you're in a 60-day grace period or approaching an OPT expiration, ask Google's immigration team whether they'll file with USCIS premium processing. Adjudication under that track runs within 15 business days, which can be critical for bridging status gaps.
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Find Senior ML Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for Senior ML Engineers?
Yes, Google sponsors H-1B visas for Senior ML Engineers. The process follows the standard USCIS cap-subject lottery, with registration in mid-March and an October 1 start date if selected. Google has dedicated immigration counsel and coordinates the petition process internally, so you won't need to manage USCIS filings independently once you have an offer.
Which visa types does Google commonly use for Senior ML Engineer roles?
Google sponsors H-1B visas for the broadest pool of international candidates, H-1B1 visas for Chilean and Singaporean nationals, and E-3 visas for Australian citizens. Each carries different timelines and lottery exposure. H-1B1 and E-3 are not subject to the annual cap, which makes them significantly faster options if you qualify by nationality.
What qualifications does Google expect for Senior ML Engineer roles?
Google's Senior ML Engineer bar typically requires a bachelor's degree or higher in computer science, machine learning, or a related engineering field, plus demonstrated experience building and deploying ML systems at scale. Practical depth in areas like model optimization, distributed training, or ML infrastructure carries more weight than academic credentials alone. Prior experience with large-scale production environments is a strong differentiator.
How do I apply for Senior ML Engineer jobs at Google?
You can browse open Senior ML Engineer roles at Google through Migrate Mate, which filters listings by visa sponsorship type so you can confirm your visa category is supported before applying. Once you identify a role, applications go through Google's careers portal. Recruiters typically conduct an initial screen within two to three weeks, followed by a structured technical loop.
How do I plan my timeline around Google's visa sponsorship process?
Timeline planning depends on which visa you need. For H-1B, count backward from October 1 and ensure your offer is in place before the March registration window. For E-3 or H-1B1, consular appointments at a U.S. embassy are often bookable within a few weeks. If you're on OPT, confirm whether your start date requires cap-gap protection or a STEM OPT extension before accepting an offer.
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