H-1B1 Chile Visa Machine Learning Engineer Jobs
Machine Learning Engineer roles qualify for H-1B1 Chile visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, engineering, or a related field. Chilean nationals skip the H-1B lottery entirely, with the 1,400-visa annual cap rarely exhausted and applications handled directly at the consulate.
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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.
We are part of ML Performance and deliver AI performance solutions at Google's unparalleled scale. We achieve this through deep fleet-wide analysis, building scaling automation, and providing last-mile optimization where customization is needed. Our work directly impacts critical models, like DeepSeek, Qwen, Gemini, Gemma, improving their performance on TPUs, bridging research with real-world, high-demand applications.
Our focus point is model's performance - we use various techniques that change AI models in order to improve their performance, while keeping quality high. It involves a combination of model design, performance analysis high- and low-level coding, compilers, and hardware design.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
ROLE AND RESPONSIBILITIES
- Analyze performance and efficiency metrics to identify bottlenecks.
- Engage with Google product teams, Cloud, researchers to solve their performance problems.
- Apply parallelization and optimization techniques, such as sharding, quantization, and sparsity, to improve model performance while meeting pre-defined quality characteristics.
- Analyze and debug performance.
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 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 performance, large-scale systems data analysis, visualization tools, or debugging.
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 developing accessible technologies.
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.
We are part of ML Performance and deliver AI performance solutions at Google's unparalleled scale. We achieve this through deep fleet-wide analysis, building scaling automation, and providing last-mile optimization where customization is needed. Our work directly impacts critical models, like DeepSeek, Qwen, Gemini, Gemma, improving their performance on TPUs, bridging research with real-world, high-demand applications.
Our focus point is model's performance - we use various techniques that change AI models in order to improve their performance, while keeping quality high. It involves a combination of model design, performance analysis high- and low-level coding, compilers, and hardware design.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
ROLE AND RESPONSIBILITIES
- Analyze performance and efficiency metrics to identify bottlenecks.
- Engage with Google product teams, Cloud, researchers to solve their performance problems.
- Apply parallelization and optimization techniques, such as sharding, quantization, and sparsity, to improve model performance while meeting pre-defined quality characteristics.
- Analyze and debug performance.
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 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 performance, large-scale systems data analysis, visualization tools, or debugging.
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 developing accessible technologies.
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.
See all 126+ Machine Learning Engineer jobs
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Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Engineer
Verify your degree maps to the role
Consular officers assess whether your bachelor's degree field directly relates to machine learning engineering. A degree in computer science, mathematics, or electrical engineering clears the bar. Statistics or physics degrees may need supporting coursework documentation to establish the connection.
Target employers with active LCA filing history
Search the OFLC Wage Search to confirm a company has previously filed Labor Condition Applications for machine learning or software engineering roles. Employers already familiar with LCA certification are far less likely to stall when you raise H-1B1 Chile sponsorship in negotiations.
Use Migrate Mate to surface H-1B1 Chile employers
Filter your job search on Migrate Mate to find employers with documented H-1B1 visa Chile filing history for machine learning and engineering roles, so you're spending time on companies that have already worked through the sponsorship process rather than educating employers from scratch.
Benchmark your offer against DOL prevailing wage
Before signing an offer, run your job title and location through the OFLC Wage Search to confirm the offered salary meets the DOL prevailing wage for your wage level. An LCA will be rejected if the offered wage falls below the certified threshold, which delays your consular appointment.
Clarify the LCA timeline before accepting an offer
Ask the employer specifically how long DOL LCA certification typically takes on their end. Standard certification runs about seven business days, but employers filing for the first time may need additional lead time to register in the FLAG system and prepare supporting documentation.
Pull your O*NET occupation profile before interviews
Review the O*NET profile for Machine Learning Engineer or the closest matching occupation to understand the official degree requirements and job duties the consular officer will reference. Framing your experience using language aligned with O*NET strengthens your specialty occupation argument during the interview.
Frequently Asked Questions
Does a machine learning engineer role qualify as a specialty occupation for the H-1B1 Chile visa?
Yes. Machine learning engineering requires at least a bachelor's degree in computer science, mathematics, engineering, or a closely related field, which satisfies the specialty occupation definition. You'll want to ensure your offer letter and any employer documentation describe duties that require that theoretical and practical application of those disciplines, not just general software development tasks.
How does the H-1B1 Chile visa differ from H-1B for machine learning engineers?
The H-1B1 Chile visa has no lottery, a dedicated annual cap of 1,400 for Chilean nationals that rarely fills, and is processed at the consulate rather than through USCIS petition. You don't need an I-129 petition, which removes several months of waiting. The trade-off is that the H-1B1 does not allow dual intent, so you cannot simultaneously pursue a green card while on H-1B1 status.
Can I find machine learning engineer employers who sponsor H-1B1 Chile visas through Migrate Mate?
Yes. Migrate Mate lets you filter specifically for employers with H-1B1 Chile filing history in engineering and machine learning roles, so you're targeting companies that have already worked through the LCA and consular process rather than approaching employers who have no experience with this visa category.
What does the employer actually file for an H-1B1 Chile visa sponsorship?
The employer files a Labor Condition Application with the DOL through the FLAG system. DOL must certify the LCA, which typically takes about seven business days. Once certified, you take that LCA along with your job offer and supporting credentials to your consular interview. There's no USCIS petition stage, which is the key procedural difference from the H-1B process.
Can I renew my H-1B1 Chile visa if my machine learning engineering project extends beyond the initial period?
H-1B1 Chile status is granted in one-year increments and can be renewed indefinitely as long as you maintain a qualifying job offer and your employer files a new certified LCA for each renewal period. There's no statutory maximum on renewals, so long-term employment at the same company is straightforward provided the role continues to meet specialty occupation requirements.
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