H-1B1 Singapore Visa Senior ML Engineer Jobs
Senior ML Engineer roles qualify for H-1B1 Singapore visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, machine learning, or a related field. No lottery, no USCIS petition filing, you apply directly at the U.S. consulate in Singapore with a certified Labor Condition Application from your employer.
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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 Senior ML Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa Senior ML Engineer Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as a Senior ML Engineer
Verify your degree maps to the role
H-1B1 visa requires your specific degree field to match the specialty occupation. A computer science or electrical engineering degree maps cleanly to Senior ML Engineer roles, but a general business or mathematics degree alone may require supporting documentation from your employer.
Target employers with active LCA filings
Search DOL's OFLC Wage Search to find companies that have filed Labor Condition Applications for ML Engineer or related titles. Prior LCA activity signals the employer already understands H-1B1 Singapore sponsorship mechanics, cutting weeks off your onboarding process.
Search verified H-1B1 sponsoring employers on Migrate Mate
Migrate Mate filters Senior ML Engineer roles by employers with documented H-1B1 Singapore sponsorship history, so you're not wasting interviews on companies that have never navigated the consular filing route for Singaporean nationals.
Confirm your offer letter names a fixed worksite
LCA certification ties wages to a specific work location. If your role is remote or multi-site, your employer must file a separate LCA for each primary worksite, clarify this before signing, since it affects DOL certification timelines and your consulate appointment package.
Use O*NET to align your resume to the occupation definition
Consular officers assess whether your duties match the specialty occupation definition. Pull the O*NET occupation profile for Software Developers or Computer and Information Research Scientists and mirror its task language in your resume and employer support letter.
Request a two-year annotation and plan your renewal before month 18
H-1B1 Singapore visas are granted in one-year or two-year increments. Ask your employer to structure the filing for the maximum two-year period, then initiate renewal paperwork at least 45 days before expiry to avoid gaps in authorized stay.
Frequently Asked Questions
Does a Senior ML Engineer role qualify as a specialty occupation for H-1B1 Singapore?
Yes. Senior ML Engineer positions require at least a bachelor's degree in computer science, electrical engineering, or a directly related field, which satisfies the specialty occupation definition under the H-1B1 visa program. Your employer confirms the degree requirement in the Labor Condition Application, and the consular officer reviews that the role genuinely requires that level of education.
How is the H-1B1 Singapore visa different from the H-1B for ML Engineer roles?
The H-1B visa requires USCIS to approve a petition before you can apply, is subject to an annual lottery, and has an 85,000-cap that regularly oversubscribes. The H-1B1 Singapore skips the lottery and the USCIS petition entirely. Your employer files a Labor Condition Application with DOL, then you apply directly at the U.S. consulate in Singapore. The 5,400 annual cap rarely fills, so timing is not a constraint for most applicants.
How do I find Senior ML Engineer jobs where the employer already understands H-1B1 Singapore sponsorship?
Migrate Mate surfaces Senior ML Engineer roles filtered by employers with verified H-1B1 Singapore sponsorship history, so you can focus your search on companies that have already filed LCAs for Singaporean nationals rather than educating hiring managers about a visa category they've never encountered.
Can I start working immediately after my consulate interview is approved?
Not immediately. After a visa issuance decision, your passport is returned with the visa stamp, which you then use to enter the United States. You can begin work on the employment start date listed in your LCA and employer offer letter. Build in time for passport return, travel, and any administrative processing delays before committing to a start date with your employer.
What happens to my H-1B1 status if my employer terminates my Senior ML Engineer role?
H-1B1 Singapore status is employer-specific and tied to the certified LCA. If your employment ends, your authorized stay ends with it and there is no formal grace period equivalent to the H-1B's 60-day portability window. You would need to either depart the United States, secure a new employer willing to file a fresh LCA and support a new consular application, or transition to a different status before your authorized period expires.