ML Engineer Jobs at Google with Visa Sponsorship
ML Engineer jobs at Google span research, applied science, and production infrastructure, with the company sponsoring H-1B visa, H-1B1 visa, 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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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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
As a part of the Discover Personalization team, you will help people feel positively connected and informed about the world around them by delivering the pulse of the Internet that matters to you, within Google Search. You will contribute to the key product's appeal, which lies in having an understanding of users and will be laser focused on building foundational user models for users using all of their interactions across Google products, and leveraging them to power Discover’s retrieval and ranking. You will manage some of the toughest ML and Quality problems, including Neural Deep Retrieval, Activity Clustering, Reinforcement Learning and Multi-Objective Ranking.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
ROLE AND RESPONSIBILITIES
- Design and implement personalized user models to optimize for user happiness, including Neural Deep Retrieval Models, Deep Neural Network Ranking/Scoring models, User/Content Clustering Models, Large Language Models (LLM)-based Retrieval Augmented Generation Models, and more.
- Build user and content clustering models to enable core personalization and ranking use cases.
- Enhance model performance and personalization precision/recall through advanced modeling techniques such as transformers, distillation, reward shaping, multi-task learning, neural bandits, etc. and capabilities through feature engineering, automatic parameter tuning, label quality engineering, etc.
- Scale the model's applications to a multitude of modalities (content, queries, videos and notifications) and use cases (retrieval, ranking, content generation, diversification, etc.).
- Create next-generation realtime ML models that can capture new user interests and world trends in seconds and scale model training and serving to billions of users.
BASIC QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
PREFERRED QUALIFICATIONS
- 8 years of experience with data structures and algorithms.
- 6 years of ML or Quality experience working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, deep model.
- Experience in C++, Dremel/F1 and TensorFlow.
- Experience working with research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
COMPENSATION
- Salary Range: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
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
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.
Distinguish your visa type before applying
Google sponsors H-1B, H-1B1 visa, and E-3 visas, and each has different timelines and filing requirements. If you're Australian, the E-3 avoids the H-1B lottery entirely. Know which category applies to you before your offer conversation starts.
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.
Prepare for H-1B cap timing if you're not exempt
If you're not currently on OPT or another cap-exempt status, H-1B registration opens in March for an October 1 start. USCIS runs a lottery when registrations exceed the 85,000 cap, so build your job search timeline around that window.
Frequently 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 visa, 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.