H-1B1 Singapore Visa ML Research Engineer Jobs
ML Research 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. The H-1B1 has no lottery, a 5,400 annual cap that rarely fills, and processes at the U.S. consulate in Singapore rather than through USCIS.
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Get Access To All JobsINTRODUCTION
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
JOB DESCRIPTION
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
You’ll play a critical role in scaling our ML Infrastructure, optimizing AI training and inference systems, and driving innovations that make Snapchat’s ranking and recommendation systems more efficient and impactful.
We’re looking for a Software Engineer, ML Infrastructure to join Snap Inc!
Responsibilities:
- Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
- Work on state-of-the-art vector search algorithms to improve the precision, recall and scalability of our retrieval systems
- Work closely with ML engineers to deploy cutting-edge models into production
KNOWLEDGE, SKILLS & ABILITIES:
- Strong programming skills in Python, Java, Scala or C++
- Strong problem-solving skills with a focus on system performance, scalability, and efficiency
- Good understanding of distributed systems and the infrastructure components of large-scale ML
- Experience with big data processing frameworks such as Spark, Flink, or Ray
- Ability to collaborate and work well with others
- Proven track record of operating highly-available systems at significant scale
- Ability to proactively learn new concepts and apply them at work
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in a technical field such as computer science or equivalent experience
- 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ years of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience
- Experience building large scale production machine learning systems, distributed systems or big data processing
PREFERRED QUALIFICATIONS:
- Masters/PhD in a technical field such as computer science or equivalent industry experience
- Experience working with ML Training platforms or optimizing AI model inference
- Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
OUR BENEFITS:
Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
COMPENSATION
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
Zone A (CA, WA, NYC):
The base salary range for this position is $209,000-$313,000 annually.
Zone B:
The base salary range for this position is $199,000-$297,000 annually.
Zone C:
The base salary range for this position is $178,000-$266,000 annually.
This position is eligible for equity in the form of RSUs.
INTRODUCTION
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
JOB DESCRIPTION
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
You’ll play a critical role in scaling our ML Infrastructure, optimizing AI training and inference systems, and driving innovations that make Snapchat’s ranking and recommendation systems more efficient and impactful.
We’re looking for a Software Engineer, ML Infrastructure to join Snap Inc!
Responsibilities:
- Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
- Work on state-of-the-art vector search algorithms to improve the precision, recall and scalability of our retrieval systems
- Work closely with ML engineers to deploy cutting-edge models into production
KNOWLEDGE, SKILLS & ABILITIES:
- Strong programming skills in Python, Java, Scala or C++
- Strong problem-solving skills with a focus on system performance, scalability, and efficiency
- Good understanding of distributed systems and the infrastructure components of large-scale ML
- Experience with big data processing frameworks such as Spark, Flink, or Ray
- Ability to collaborate and work well with others
- Proven track record of operating highly-available systems at significant scale
- Ability to proactively learn new concepts and apply them at work
MINIMUM QUALIFICATIONS:
- Bachelor’s degree in a technical field such as computer science or equivalent experience
- 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ years of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience
- Experience building large scale production machine learning systems, distributed systems or big data processing
PREFERRED QUALIFICATIONS:
- Masters/PhD in a technical field such as computer science or equivalent industry experience
- Experience working with ML Training platforms or optimizing AI model inference
- Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
OUR BENEFITS:
Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
COMPENSATION
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
Zone A (CA, WA, NYC):
The base salary range for this position is $209,000-$313,000 annually.
Zone B:
The base salary range for this position is $199,000-$297,000 annually.
Zone C:
The base salary range for this position is $178,000-$266,000 annually.
This position is eligible for equity in the form of RSUs.
See all 804+ H-1B1 Singapore Visa ML Research Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa ML Research Engineer Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as a ML Research Engineer
Verify your degree meets specialty occupation requirements
ML Research Engineer roles require a directly related degree field. A general computer science degree typically qualifies, but a business or unrelated STEM degree may not. Cross-check your credentials against the O*NET occupation profile for this role before applying.
Target employers with active H-1B1 LCA filings
Search Migrate Mate to identify employers who have filed Labor Condition Applications for H-1B1 Singapore roles. DOL disclosure data shows which companies have sponsored Singaporean nationals in ML and research engineering positions.
Distinguish your research profile from software engineering candidates
Employers often conflate ML Research Engineers with software engineers and assume H-1B lottery exposure. Frame your resume around publications, model architectures, and research outcomes to signal the specialized role that justifies H-1B1 visa sponsorship without lottery risk.
Confirm the employer files LCAs before accepting any offer
Your employer must file a certified Labor Condition Application with DOL before your H-1B1 petition is submitted. Ask your recruiter early whether the company has sponsored H-1B1 Singapore employees before, not just H-1B holders generally.
Use OFLC Wage Search to benchmark your offer against prevailing wage
DOL requires employers to pay at least the prevailing wage for your occupation and work location. Run the OFLC Wage Search using the correct SOC code for ML Research Engineer before your offer letter is finalized so you can spot underpayment before it becomes a compliance issue.
Apply at the Singapore consulate rather than adjusting status
H-1B1 Singapore visa applications are processed through consular processing in Singapore, not through USCIS change-of-status filings. Plan your timeline around consulate appointment availability, which is typically shorter than USCIS adjudication windows for standard H-1B petitions.
Frequently Asked Questions
Does an ML Research Engineer role qualify as a specialty occupation for the H-1B1 Singapore visa?
Yes. ML Research Engineer roles require at minimum a bachelor's degree in computer science, machine learning, statistics, or a directly related field, which meets the specialty occupation definition for H-1B1 visa purposes. Roles that blend research with software engineering still qualify as long as the position requires a specific theoretical or technical degree, not just any STEM background.
How does the H-1B1 Singapore visa compare to the H-1B for ML Research Engineer positions?
The H-1B1 Singapore visa has no lottery, so there's no randomized selection cutting you out of the process. The annual cap of 5,400 has never been exhausted, meaning qualified Singaporean nationals can apply any time of year. The H-1B, by contrast, is subject to an annual lottery with selection rates well below 50% for most applicants, making the H-1B1 a structurally more reliable path for Singaporeans in ML research roles.
Which employers are most likely to sponsor H-1B1 Singapore visas for ML Research Engineers?
Employers who already sponsor H-1B holders for machine learning and AI research roles are the most likely to extend that process to H-1B1 Singapore applicants, since the employer-side LCA filing process is similar. Use Migrate Mate to filter for companies with verified H-1B1 LCA filing history in ML and research engineering occupations rather than relying on general employer reputation.
Can I switch employers after starting work on an H-1B1 Singapore visa?
Yes, but the new employer must file a fresh LCA with DOL and submit a new H-1B1 visa petition before you begin work. Unlike H-1B portability under AC21, H-1B1 does not allow you to start with a new employer the moment a transfer petition is filed. Plan your transition timeline with at least several weeks of lead time before your intended start date with the new company.
How long does H-1B1 Singapore visa processing take for ML Research Engineer roles?
Once the employer's LCA is certified by DOL, the consular appointment and visa stamp process in Singapore is generally faster than USCIS adjudication for standard H-1B petitions. Consulate processing for H-1B1 visa applications typically runs a few weeks from interview to passport return, though administrative processing for research roles with security-sensitive technology backgrounds can extend that timeline. Confirm current wait times with USCIS and the U.S. Embassy Singapore before committing to a start date.