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
Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), software engineers build the systems that connect generative models, scientific data, and experimental workflows into reliable, production-grade pipelines powering Lila's protein design and engineering campaigns.
We're hiring a Staff ML Engineer, Life Sciences AI to lead software infrastructure development for our protein design and engineering pipelines. This is a senior IC role focused on the engineering systems that surround and support our ML stack — pipeline orchestration, data flow between computational and experimental systems, integration of new tools and methods, and the developer experience that lets LSAI move fast on commercial partnership deliverables.
What You'll Be Building
- Architect and build software infrastructure powering Lila's protein design and engineering pipelines: orchestration, data flow, APIs, and integration with experimental systems.
- Own the engineering side of LSAI's "Lab-in-the-Loop" lifecycle — connecting computational outputs to experimental inputs and feeding results back into design workflows.
- Onboard new tools and methods developed by AI scientists and ML engineers into production-ready systems used in commercial partnership campaigns.
- Partner cross-functionally with ML researchers, scientists, and platform engineers to translate research code into reliable, scalable systems.
- Set engineering standards for LSAI software — design reviews, CI/CD, testing, observability, reproducibility — and mentor senior engineers as the team grows.
- Diagnose and resolve reliability, performance, and scaling bottlenecks in production pipelines supporting partnership deliverables.
What You’ll Need to Succeed
- Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience).
- 8+ years of professional software engineering experience in Python (or comparable systems languages).
- Proven experience designing, building, and operating scalable production systems — APIs, data pipelines, orchestration, and cloud infrastructure.
- Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices.
- Experience building or operating scientific or ML-adjacent infrastructure — workflow orchestration, experiment tracking, and reproducible pipelines.
- Hands-on experience with containerization, orchestration platforms, and infrastructure-as-code on a major cloud provider.
- Track record of leading technical direction across multiple systems and partnering deeply with research scientists or ML engineers to translate scientific needs into production engineering.
Bonus Points For
- Experience building infrastructure for protein design and engineering, antibody engineering, or other molecular ML applications.
- Familiarity with biological data formats and bioinformatics tooling.
- Experience integrating ML training/inference systems with broader product or scientific platforms.
- Open-source contributions to scientific computing or data infrastructure projects.
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
$162,800 - $200,200 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
Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), software engineers build the systems that connect generative models, scientific data, and experimental workflows into reliable, production-grade pipelines powering Lila's protein design and engineering campaigns.
We're hiring a Staff ML Engineer, Life Sciences AI to lead software infrastructure development for our protein design and engineering pipelines. This is a senior IC role focused on the engineering systems that surround and support our ML stack — pipeline orchestration, data flow between computational and experimental systems, integration of new tools and methods, and the developer experience that lets LSAI move fast on commercial partnership deliverables.
What You'll Be Building
- Architect and build software infrastructure powering Lila's protein design and engineering pipelines: orchestration, data flow, APIs, and integration with experimental systems.
- Own the engineering side of LSAI's "Lab-in-the-Loop" lifecycle — connecting computational outputs to experimental inputs and feeding results back into design workflows.
- Onboard new tools and methods developed by AI scientists and ML engineers into production-ready systems used in commercial partnership campaigns.
- Partner cross-functionally with ML researchers, scientists, and platform engineers to translate research code into reliable, scalable systems.
- Set engineering standards for LSAI software — design reviews, CI/CD, testing, observability, reproducibility — and mentor senior engineers as the team grows.
- Diagnose and resolve reliability, performance, and scaling bottlenecks in production pipelines supporting partnership deliverables.
What You’ll Need to Succeed
- Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience).
- 8+ years of professional software engineering experience in Python (or comparable systems languages).
- Proven experience designing, building, and operating scalable production systems — APIs, data pipelines, orchestration, and cloud infrastructure.
- Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices.
- Experience building or operating scientific or ML-adjacent infrastructure — workflow orchestration, experiment tracking, and reproducible pipelines.
- Hands-on experience with containerization, orchestration platforms, and infrastructure-as-code on a major cloud provider.
- Track record of leading technical direction across multiple systems and partnering deeply with research scientists or ML engineers to translate scientific needs into production engineering.
Bonus Points For
- Experience building infrastructure for protein design and engineering, antibody engineering, or other molecular ML applications.
- Familiarity with biological data formats and bioinformatics tooling.
- Experience integrating ML training/inference systems with broader product or scientific platforms.
- Open-source contributions to scientific computing or data infrastructure projects.
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
$162,800 - $200,200 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.
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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-1B visa1 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 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.
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