H-1B1 Singapore Visa ML Engineer Jobs
ML Engineer jobs with H-1B1 Singapore visa sponsorship are accessible to Singaporean nationals without a lottery or USCIS petition. The 5,400-visa annual cap rarely fills, and your employer files the Labor Condition Application directly through DOL before you apply at the U.S. consulate in Singapore.
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Get Access To All JobsYour Impact at LILA
This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity of scientific use cases in materials, chemistry, and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today’s greatest challenges in physical sciences.
What You'll Be Building
- Design, implement, and maintain end‑to‑end ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
- Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
- Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
- Contribute to technical design reviews, coding standards, and mentoring of best practices.
What You’ll Need To Succeed
- BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
- Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
- Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
- Hands-on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
- Clear communication and collaboration in cross-functional settings.
Bonus Points For
- Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
- GPU optimization experience (CUDA, Triton, compilation, distributed training).
- Prior contributions to open-source ML or scientific software.
- Experience with workflow orchestration, data provenance, or large-scale compute environments.
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits.
Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company-wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office-based employees; and a company subsidized lunch program.
International Benefits.
Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range:
$128,000 USD - $198,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is 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. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Your Impact at LILA
This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity of scientific use cases in materials, chemistry, and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today’s greatest challenges in physical sciences.
What You'll Be Building
- Design, implement, and maintain end‑to‑end ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
- Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
- Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
- Contribute to technical design reviews, coding standards, and mentoring of best practices.
What You’ll Need To Succeed
- BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
- Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
- Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
- Hands-on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
- Clear communication and collaboration in cross-functional settings.
Bonus Points For
- Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
- GPU optimization experience (CUDA, Triton, compilation, distributed training).
- Prior contributions to open-source ML or scientific software.
- Experience with workflow orchestration, data provenance, or large-scale compute environments.
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits.
Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company-wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office-based employees; and a company subsidized lunch program.
International Benefits.
Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range:
$128,000 USD - $198,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is 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. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
See all 646+ H-1B1 Singapore Visa ML Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa ML Engineer Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as a ML Engineer
Frame your ML credentials for specialty occupation
Your offer letter and degree must establish that the ML Engineer role requires a specific technical field of study. A bachelor's in computer science or statistics works; a general business degree usually doesn't, even with years of ML experience.
Search LCA filings to find H-1B1-ready employers
Use Migrate Mate to filter job listings by employers with verified H-1B1 Singapore LCA filing history, so you're targeting companies that have already completed the DOL process for Singaporean nationals in technical roles.
Check prevailing wage before negotiating your offer
Your employer must pay at least the DOL prevailing wage for your ML Engineer role in their location. Run the OFLC Wage Search before your offer conversation so you know the wage floor and can negotiate from an informed position.
Confirm your employer's E-Verify enrollment early
E-Verify participation isn't required for all H-1B1 visa employers, but many ML-heavy companies are already enrolled due to federal contracting obligations. Confirming enrollment before accepting an offer prevents delays if your employer needs to register first.
Use O*NET to document specialty occupation alignment
ML Engineer maps to specific SOC codes in O*NET that list degree requirements in a directly related field. Sharing the O*NET occupation profile with your employer's HR team speeds up LCA preparation and reduces back-and-forth on job description language.
Time your consulate appointment around LCA certification
DOL certifies the LCA in about seven business days. Schedule your U.S. consulate appointment in Singapore only after certification is confirmed, since you must present the certified LCA at the interview to proceed.
Frequently Asked Questions
Does an ML Engineer role qualify as a specialty occupation for the H-1B1 Singapore visa?
Yes. ML Engineer roles consistently qualify because they require a bachelor's degree or higher in a directly related technical field, such as computer science, mathematics, or statistics. The DOL Labor Condition Application and your offer letter together establish that connection. Generic titles like 'data analyst' require more documentation, but ML Engineer with a technical degree is a strong fit for the specialty occupation standard.
How does the H-1B1 Singapore visa differ from the H-1B for ML Engineers?
The H-1B1 Singapore visa skips the H-1B lottery entirely and has a separate 5,400-visa annual cap that has never been exhausted. Your employer still files a Labor Condition Application with DOL, but there's no USCIS petition. You apply directly at the U.S. consulate in Singapore. The trade-off is that H-1B visa1 doesn't carry dual intent, so you'll need to demonstrate nonimmigrant intent at each renewal.
How do I find ML Engineer employers who will sponsor the H-1B1 Singapore visa?
Use Migrate Mate to search for ML Engineer roles filtered by employers with verified H-1B1 Singapore LCA filing history. That data comes from DOL disclosure records, so you're identifying companies that have already completed the filing process for Singaporean nationals, not just ones that claim to sponsor visas in job descriptions.
Can I switch ML Engineer employers after arriving on an H-1B1 Singapore visa?
Yes, but each new employer must file a fresh Labor Condition Application with DOL before you begin working for them. Unlike H-1B portability under AC21, H-1B1 visa doesn't allow you to start work with a new employer while the application is pending. Plan the transition so your new employer's LCA is certified and your updated visa is in hand before you leave your current role.
What happens to my H-1B1 Singapore status if my ML Engineer role is reclassified or my project scope changes significantly?
If your employer materially changes your job duties to the point that the role no longer matches the certified Labor Condition Application, they need to file an amended LCA. This matters for ML Engineers who shift from research roles into product management or general software engineering. Document the technical nature of your work continuously, and flag significant title or duty changes to your employer's HR team so the LCA stays current.