H-1B1 Singapore Visa AI Engineer Jobs
AI Engineer jobs with H-1B1 Singapore visa sponsorship let you skip the H-1B lottery entirely. As a Singaporean national, you apply directly at the U.S. consulate under the U.S.-Singapore Free Trade Agreement, with an annual cap of 5,400 visas that has never come close to filling.
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Get Access To All JobsAI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS)
CSQ327R177
The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.
The impact you will have:
- Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
- Own production rollouts of consumer and internally facing GenAI applications.
- Serve as a trusted technical advisor to customers across a variety of domains.
- Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
- Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.
What we look for:
- Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
- Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
- Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
- Passion for collaboration, life-long learning, and driving business value through AI.
- [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$152,900 — $210,155 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS)
CSQ327R177
The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.
The impact you will have:
- Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
- Own production rollouts of consumer and internally facing GenAI applications.
- Serve as a trusted technical advisor to customers across a variety of domains.
- Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
- Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.
What we look for:
- Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
- Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
- Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
- Passion for collaboration, life-long learning, and driving business value through AI.
- [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$152,900 — $210,155 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
See all 696+ H-1B1 Singapore Visa AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa AI Engineer Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as an AI Engineer
Verify your role qualifies as specialty occupation
The H-1B1 visa requires your AI Engineer position to demand a bachelor's degree or higher in a directly related field. Cross-check your offer letter's duties against the O*NET profile for your SOC code before signing anything.
Translate your NUS or NTU transcript for U.S. recruiters
Many U.S. hiring managers don't recognize Singapore's degree structure. A credential evaluation from a NACES-approved evaluator confirms your qualification meets the specialty occupation standard consular officers apply.
Search for employers with active H-1B1 LCA filings
Employers who've filed Labor Condition Applications for H-1B1 Singapore roles have already navigated DOL certification. Use Migrate Mate to filter AI Engineer roles by verified H-1B1 LCA filing history instead of cold-applying to unknown sponsors.
Ask recruiters whether the role is cap-exempt eligible
Certain employers, including nonprofit research institutions and universities, file outside the 5,400 annual cap. If your AI Engineer role is research-focused, confirm cap-exempt status early so the cap never becomes a scheduling constraint.
Request the LCA before your consulate appointment is booked
Your employer must file and receive DOL certification on the LCA before you can apply at the consulate. Delays here are the most common reason H-1B1 visa timelines slip, so confirm the LCA certification date in writing upfront.
Benchmark your offered salary against OFLC Wage Search
The LCA must certify you'll be paid at least the prevailing wage for your SOC code and work location. Run your job title and city through OFLC Wage Search yourself so you can flag a non-compliant offer before the employer files.
Frequently Asked Questions
Does an AI Engineer role qualify for the H-1B1 Singapore visa?
Yes, provided the position requires at least a bachelor's degree in computer science, artificial intelligence, machine learning, or a directly related field. Generic titles like 'AI Engineer' vary widely, so the consular officer will look at the actual duties. Roles requiring original model development, neural architecture design, or ML infrastructure engineering consistently satisfy the specialty occupation standard.
How does the H-1B1 Singapore visa compare to H-1B for AI Engineers?
The H-1B1 visa has no lottery, so you're not gambling on a roughly 25% selection rate the way H-1B applicants are. The 5,400 annual cap for Singaporeans has never been exhausted, and you apply directly at the U.S. consulate rather than waiting for USCIS to adjudicate a petition. The tradeoff is that H-1B1 doesn't confer dual intent, meaning it's harder to pursue a green card concurrently from this status.
How do I find AI Engineer employers who actually sponsor H-1B1 Singapore visas?
Migrate Mate filters AI Engineer roles by verified H-1B1 visa Labor Condition Application filing history pulled from DOL disclosure data, so you can see which employers have already completed the DOL certification process for Singaporean hires. This cuts out the guesswork of approaching companies that haven't sponsored the visa type before and may not know how.
What documents do Singaporean AI Engineers need for the consulate interview?
You'll need your certified LCA, a support letter from your employer detailing your duties and qualifications, your academic transcripts and degree certificate, and your DS-160 confirmation. If your Singapore degree is a three-year program, bring a credential evaluation from a NACES-recognized evaluator to preempt any question about equivalency to a U.S. four-year bachelor's degree.
Can I switch AI Engineer employers after arriving on an H-1B1 Singapore visa?
Yes, but your new employer must file a fresh LCA with DOL and receive certification before you start working. There's no H-1B-style portability that lets you begin work on a pending application. You're authorized to work only once the new LCA is certified and your status reflects the new employer, so plan for a gap between offer acceptance and your start date.