Machine Learning Manager Jobs at Google with Visa Sponsorship
Machine Learning Manager jobs at Google sit at the intersection of research leadership and product impact, overseeing teams building large-scale ML systems across Search, Ads, Cloud, and DeepMind. Google has a well-established infrastructure for sponsoring H-1B visa, H-1B1 visa, and E-3 visas for engineering and ML leadership roles.
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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 Machine Learning Manager Jobs at Google
Frame your ML leadership portfolio strategically
Google's hiring bar for ML Managers emphasizes both technical depth and cross-functional influence. Document shipped models, team growth, and measurable system improvements before applying. Interviewers probe whether you can lead research and drive production impact simultaneously.
Target teams with active LCA filings
Search DOL's OFLC disclosure data for Google LLC LCA filings under job titles like 'Machine Learning Manager' or 'Engineering Manager, ML.' This surfaces which Google product areas are actively hiring sponsored roles right now, not just historically.
Understand Google's internal transfer sponsorship rules
If you receive a return offer after an internship or contractor stint at Google, ask HR explicitly whether your offer package includes H-1B cap-exempt filing or a cap-subject petition. These pathways have different USCIS timelines and filing windows.
Align your visa category to your citizenship early
Australian citizens applying for ML Manager roles should flag E-3 eligibility to Google's immigration team before offer finalization. E-3 processing bypasses the H-1B lottery entirely, which shortens your timeline to U.S. start date by several months.
Use Migrate Mate to filter Google ML roles by sponsorship type
Search Migrate Mate to browse open Machine Learning Manager positions at Google filtered by the visa types they sponsor. This lets you target the specific team and role level where sponsorship is confirmed before you invest time in the interview process.
Prepare for USCIS specialty occupation scrutiny
ML Manager petitions can draw USCIS Requests for Evidence if the role description blurs managerial and individual-contributor duties. Work with Google's immigration counsel to ensure the job description clearly ties a specific bachelor's degree field to the core management function.
Frequently Asked Questions
Does Google sponsor H-1B visas for Machine Learning Managers?
Yes, Google sponsors H-1B visas for Machine Learning Manager roles. Google is a registered H-1B employer and files petitions for engineering leadership positions including ML management. Because the H-1B is subject to an annual cap and lottery, timing your application cycle matters. Google's immigration team coordinates filing windows with USCIS's April 1 start date, so your offer timeline will be built around that calendar.
Which visa types does Google commonly use for Machine Learning Manager roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for Machine Learning Manager positions. H-1B is the most widely used pathway. H-1B1 is available to Chilean and Singaporean nationals without lottery exposure. E-3 applies exclusively to Australian citizens and also bypasses the H-1B lottery, making it a faster path to a U.S. start date for eligible candidates.
What qualifications does Google expect for a Machine Learning Manager role?
Google typically requires a bachelor's degree or higher in Computer Science, Machine Learning, or a closely related field, alongside hands-on experience leading ML teams that have shipped production systems at scale. Interviewers assess both technical depth, specifically model architecture and infrastructure decisions, and leadership scope. Candidates without a directly relevant degree can sometimes substitute equivalent experience, but this requires stronger documentation for the H-1B specialty occupation standard.
How do I apply for Machine Learning Manager jobs at Google?
Applications go through Google's careers portal at careers.google.com, but surfacing the right open roles by team and sponsorship type takes extra research. Migrate Mate lets you browse confirmed Machine Learning Manager openings at Google filtered by visa sponsorship category, so you can identify which specific teams are hiring sponsored candidates before you apply. Once you apply, Google's process typically includes recruiter screen, technical phone interviews, and an onsite or virtual loop.
How do I plan my timeline when pursuing an H-1B sponsored role at Google?
H-1B cap-subject petitions must be filed during the USCIS registration window each March, with employment starting no earlier than October 1. If you're on F-1 OPT, your start date can precede October 1 under your existing work authorization, but Google will still file the H-1B petition to cover you once OPT expires. Factor in at least six months from offer acceptance to confirmed H-1B status, and confirm with Google's immigration team whether premium processing is available for your petition.