ML Software Engineer Jobs at Google with Visa Sponsorship
ML Software Engineer jobs at Google sit at the center of building ML infrastructure and research products used across billions of users. The company has a structured sponsorship process for H-1B visa, H-1B1 visa, and E-3 visa candidates, with a dedicated immigration team that manages petitions from offer through filing.
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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 Software Engineer Jobs at Google
Align your portfolio with Google's ML stack
Google's ML roles emphasize experience with large-scale distributed training, TensorFlow, and JAX. Publish projects or research on GitHub that demonstrate production-level ML work, not just model notebooks. Interviewers assess systems thinking alongside modeling skill.
Target teams with open research headcount
Google Brain, DeepMind, and core Search ML teams hire internationally and have established sponsorship workflows. Filtering your search to these orgs increases the chance your hiring manager has sponsored candidates before and knows the internal process.
Clarify your visa category before the offer stage
Australian citizens should confirm E-3 eligibility early in recruiter conversations. Google sponsors all three work visa types for ML roles, but the internal filing process differs by category. Knowing which applies to you lets you ask the right questions before signing.
Use Migrate Mate to find open ML roles at Google
ML Software Engineer openings at Google that include visa sponsorship are consolidated on Migrate Mate, so you can filter specifically for sponsored roles rather than sorting through listings that exclude international candidates.
Prepare for Google's structured ML interview format
Google's ML hiring loop includes a coding round, an ML fundamentals round, and a system design round focused on ML pipelines. Practicing these three formats specifically, not general SWE interview prep, determines whether you clear the loop and reach offer stage where sponsorship is confirmed.
Confirm your H-1B timeline against the April lottery
If you need H-1B status, USCIS registration opens in March and the lottery runs in April. Google's immigration team works within that window, so aligning your offer acceptance and start date expectations to the cap-subject timeline avoids a delayed start or a gap in authorization.
Frequently Asked Questions
Does Google sponsor H-1B visas for ML Software Engineers?
Yes, Google sponsors H-1B visas for ML Software Engineers. The company has an internal immigration team that manages USCIS petition filing, including premium processing when timelines require it. If you're subject to the H-1B cap, your offer needs to align with the April registration window. Cap-exempt scenarios, such as transferring from a university or research institution, follow a different timeline.
Which visa types does Google sponsor for ML Software Engineer roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for ML Software Engineer positions. H-1B is available to most nationalities and subject to the annual cap and lottery. H-1B1 is available only to citizens of Chile and Singapore. E-3 is available only to Australian citizens and has its own separate annual allocation with no lottery. Your eligibility depends on your citizenship.
What qualifications does Google expect for ML Software Engineer roles?
Google's ML Software Engineer roles typically require a bachelor's degree or higher in computer science, machine learning, or a related field, with demonstrated experience building and deploying ML systems at scale. Familiarity with TensorFlow, JAX, or PyTorch is expected. Research publication history strengthens applications for senior and research-adjacent roles. Practical system design experience, not just modeling knowledge, is assessed throughout the interview loop.
How do I apply for ML Software Engineer jobs at Google?
You can browse ML Software Engineer openings at Google through Migrate Mate, which filters specifically for roles that include visa sponsorship. Once you identify a role, you apply directly through Google's careers portal. After an initial recruiter screen, the process moves through a technical phone screen and a full interview loop covering coding, ML fundamentals, and system design before an offer is extended.
How long does the visa sponsorship process take after a Google offer?
Timeline depends on your visa category. For H-1B, if you're cap-subject, the process is tied to the April lottery and an October 1 start date, which can mean a wait of several months from offer acceptance. E-3 and H-1B1 visa petitions are not cap-subject and can be filed and approved faster, sometimes within weeks. Google's immigration team initiates the process after you accept your offer and confirm your immigration status.