H-1B1 Chile Visa ML Engineer Jobs
ML Engineer jobs with H-1B1 Chile visa sponsorship are open to Chilean nationals under the U.S.-Chile Free Trade Agreement. No lottery, no USCIS filing, and the 1,400-visa annual cap rarely fills. Employers file a Labor Condition Application with DOL, and you apply directly at the consulate with your job offer in hand.
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Get Access To All JobsINTRODUCTION
Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.
As a Senior Software/Machine Learning (ML) Engineer in the Gemini Enterprise team, you will be at the heart of the generative Artificial Intelligence (AI) revolution. You won't just be testing models; you will be engineering the systems that define the intelligence, reliability, and helpfulness of Gemini Enterprise for millions of enterprise users. You will architect automated evaluation frameworks, design optimization algorithms, and solve technical issues at the intersection of Large Language Models (LLMs) and enterprise-grade software. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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.
BASIC QUALIFICATIONS:
- Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience in software development with one or more programming languages.
- 2 years of experience with core Generative Artificial Intelligence (GenAI) technologies (e.g., Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agents) or model training/post-training.
- 1 year of experience with GenAI concepts such as language modeling or computer vision.
PREFERRED QUALIFICATIONS:
- Master’s degree or PhD in Computer Science or a related technical field.
- Experience in machine learning modeling and tech leadership roles.
- Proficiency in Python, C++.
- Experience building production-grade LLM-based applications and working with Google internal infrastructure.
- Track record of innovation and critical thinking in solving technical problems.
Responsibilities:
- Lead the technical development of agentic features to transform enterprise productivity.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- 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 Generative Artificial Intelligence (GenAI) solutions, leverage Machine Learning (ML) infrastructure, and evaluate tradeoffs between different techniques and their application domains.
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 Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.
As a Senior Software/Machine Learning (ML) Engineer in the Gemini Enterprise team, you will be at the heart of the generative Artificial Intelligence (AI) revolution. You won't just be testing models; you will be engineering the systems that define the intelligence, reliability, and helpfulness of Gemini Enterprise for millions of enterprise users. You will architect automated evaluation frameworks, design optimization algorithms, and solve technical issues at the intersection of Large Language Models (LLMs) and enterprise-grade software. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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.
BASIC QUALIFICATIONS:
- Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience in software development with one or more programming languages.
- 2 years of experience with core Generative Artificial Intelligence (GenAI) technologies (e.g., Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agents) or model training/post-training.
- 1 year of experience with GenAI concepts such as language modeling or computer vision.
PREFERRED QUALIFICATIONS:
- Master’s degree or PhD in Computer Science or a related technical field.
- Experience in machine learning modeling and tech leadership roles.
- Proficiency in Python, C++.
- Experience building production-grade LLM-based applications and working with Google internal infrastructure.
- Track record of innovation and critical thinking in solving technical problems.
Responsibilities:
- Lead the technical development of agentic features to transform enterprise productivity.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- 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 Generative Artificial Intelligence (GenAI) solutions, leverage Machine Learning (ML) infrastructure, and evaluate tradeoffs between different techniques and their application domains.
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 Visa Sponsorship as a ML Engineer
Verify your degree satisfies specialty occupation
The H-1B1 visa requires a bachelor's degree or higher in a field directly related to ML engineering. A degree in computer science, electrical engineering, or applied mathematics typically qualifies. A general management or unrelated STEM degree won't, even with years of ML experience.
Pull your O*NET occupation profile before applying
ML Engineer maps to O*NET occupation 15-2051.00 under Mathematical Science Occupations. Printing that profile and matching your responsibilities to the listed tasks gives your employer concrete language to justify specialty occupation status in the LCA.
Target employers already filing LCAs for technical roles
Search Migrate Mate to find companies with active Labor Condition Application history for software and ML roles. Employers who have filed before understand the H-1B1 Chile pathway and won't stall your offer letter waiting for legal team education.
Confirm your offer letter specifies full-time employment
The H-1B1 requires a legitimate U.S. job offer for a specific role at a named employer. Part-time offers, contractor arrangements, or vague consulting agreements won't satisfy consular review. Get a formal employment letter stating your title, duties, and start date.
Check that your employer's LCA wage meets prevailing wage
DOL requires the LCA to certify a wage at or above the prevailing level for your occupation and location. Before the offer stage, run your role's wage level through the OFLC Wage Search to know what Level I through IV rates look like for ML engineers in your target city.
Use your two-year H-1B1 renewal cycle strategically
Unlike H-1B visa, the H-1B1 Chile visa doesn't lead directly to a green card filing while in status. If your employer plans to sponsor permanent residence, discuss PERM timing early so the labor certification process starts before your first renewal cycle ends.
Frequently Asked Questions
Does an ML Engineer role qualify as a specialty occupation for the H-1B1 Chile visa?
Yes. ML Engineer roles require theoretical and practical application of machine learning, statistics, and software engineering, and typically demand a bachelor's degree or higher in computer science, mathematics, or a related field. USCIS and consular officers assess specialty occupation based on the degree requirement for the specific position, not the job title alone. Your offer letter and employer documentation must tie the role's duties to that degree requirement.
How does the H-1B1 Chile visa compare to the H-1B for ML Engineer jobs?
The H-1B1 Chile visa has a dedicated annual cap of 1,400 visas for Chilean nationals, no lottery, and consular processing rather than a USCIS petition, which means faster and more predictable access to U.S. ML roles. The H-1B requires USCIS approval, is subject to an 85,000-slot lottery with a roughly 25 percent selection rate, and carries higher employer filing costs. The trade-off is that the H-1B1 doesn't support dual intent, so long-term green card planning requires separate timing.
How do I find U.S. employers willing to sponsor an H-1B1 Chile visa for an ML Engineer?
Use Migrate Mate to search for employers with active Labor Condition Application filing history in machine learning and software engineering roles. Companies that have already filed LCAs for technical positions understand the sponsorship process and are far less likely to withdraw an offer once they learn the H-1B1 requires employer LCA filing.
What documents do I need for my H-1B1 Chile consular interview as an ML Engineer?
You'll need your certified LCA from DOL, a formal job offer letter from your employer, your academic credentials showing a degree in a directly related field, your DS-160 confirmation, and valid passport. Consular officers may also ask for evidence tying your degree field to ML engineering duties, so bring transcripts or a credential evaluation if your degree title isn't an obvious match for the role.
Can I work for multiple clients or on a project basis with an H-1B1 Chile visa as an ML Engineer?
The H-1B1 is employer-specific and tied to the petitioning company named on the LCA. Consulting arrangements where you bill multiple clients or work on-site at third-party locations raise compliance questions under DOL rules. If your role involves client-facing deployment of ML models, your employer's LCA must accurately reflect the actual worksite locations, and USCIS guidance on third-party placements applies to the underlying specialty occupation determination.
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