H-1B1 Singapore Visa Machine Learning Manager Jobs
Machine Learning Manager roles qualify for H-1B1 Singapore visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, statistics, or a related field. No lottery, no USCIS petition filing, and the 5,400-visa annual cap has never been exhausted, so your timeline depends on your employer's readiness, not a random draw.
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Get Access To All JobsWe're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
Caper Carts are AI-powered, intelligent shopping carts developed by Instacart that let customers scan, weigh, and pay for items directly on the cart—eliminating checkout lines. Equipped with cameras and sensors, these carts automatically recognize items, offer personalized promotions, and feature a touchscreen for real-time, interactive shopping. This machine learning team builds the brain behind the cart.
We’re hiring an Engineering Manager, Machine Learning and Computer Vision to lead a team of talented CV, ML and AI infrastructure engineers who power perception, multimodal understanding, and edge inference for Caper Carts. You will own the roadmap for how our carts see and reason about what’s in the basket, and you’ll build the platforms and models that make checkout seamless in dynamic, real-world retail environments. Your direct team will be ~10 engineers within a broader organization of ~30 spanning Android and hardware.
This is a high-impact role at the frontier of physical AI—bridging edge devices in stores with cloud-scale data and training systems. You’ll partner closely with Android, hardware, product, and operations to deliver measurable improvements in recognition accuracy, latency, and reliability. The role is remote across Canada; West Coast time zones are ideal, but we’re open to great talent anywhere in the country. Learn more about our work at Connecting stores from edge to cloud: reinventing retail with physical AI.
About the Job
- Lead and grow a team of ~10 ML, CV and AI infrastructure engineers building the perception and reasoning systems that power Caper Carts in live retail environments.
- Define the technical vision, roadmap, and success metrics for cart perception and multimodal understanding; prioritize work that drives measurable gains in item recognition accuracy, checkout speed, and system reliability.
- Architect scalable training, data, and inference platforms on GCP using Ray, Kubernetes, and modern MLOps practices to enable rapid experimentation and safe, repeatable deployments.
- Deliver production-grade CV/VLM models for multi-camera item detection, weighing, and basket reasoning; optimize on-device inference for low-latency, high-availability operation at the edge.
- Build the data flywheel end-to-end—instrumentation, labeling, evaluation, offline/online testing, and monitoring—to continuously improve performance across diverse store conditions.
- Collaborate cross-functionally with Android, hardware, product, design, operations, and retailer partners; communicate risks, tradeoffs, and timelines clearly in a fast-paced, ever-evolving environment.
About You
Minimum Qualifications
- 8+ years of experience building and deploying machine learning systems, with a strong focus on computer vision in production environments.
- 2+ years of experience managing teams of 6+ ML/CV/AI engineers, including hiring, performance management, and career development.
- Hands-on expertise with computer vision, deep learning (e.g., PyTorch), model training/evaluation, and MLOps practices for reliable CI/CD of ML services.
- Proven experience architecting and operating ML infrastructure on GCP (e.g., GKE, Vertex AI, BigQuery) and distributed training/inference with Ray; containerization with Docker and orchestration with Kubernetes.
- Experience delivering real-time edge inference, including model optimization (e.g., TensorRT, ONNX, quantization) and monitoring for latency, throughput, and accuracy.
- Proficiency in Python and SQL, with a track record of shipping end-to-end CV systems including data pipelines, experimentation, deployment, and post-launch iteration.
- Bachelor’s degree in Computer Science, Electrical/Computer Engineering, or a related technical field, or equivalent practical experience.
Preferred Qualifications
- Experience integrating on-device ML with Android applications and collaborating closely with Android teams on SDKs and APIs.
- Background with multimodal vision-language models (VLMs) and large language models (LLMs) for perception, retrieval, or instruction-based reasoning.
- Experience with sensors and hardware integration (e.g., multi-camera setups, weight sensors), calibration, and dataset generation for robotics or retail environments.
- Demonstrated success leading cross-functional programs across 3+ partner teams and delivering multi-quarter roadmaps.
- Graduate degree (MS/PhD) in a relevant field with research or applied focus in computer vision, machine learning, or robotics.
LI-Remote
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.
For US based candidates, the base pay ranges for a successful candidate are listed below.
CA, NY, CT, NJ
$240,000 - $253,000 USD
WA
$230,000 - $243,000 USD
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
$221,000 - $233,000 USD
All other states
$201,000 - $212,000 USD
We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
Caper Carts are AI-powered, intelligent shopping carts developed by Instacart that let customers scan, weigh, and pay for items directly on the cart—eliminating checkout lines. Equipped with cameras and sensors, these carts automatically recognize items, offer personalized promotions, and feature a touchscreen for real-time, interactive shopping. This machine learning team builds the brain behind the cart.
We’re hiring an Engineering Manager, Machine Learning and Computer Vision to lead a team of talented CV, ML and AI infrastructure engineers who power perception, multimodal understanding, and edge inference for Caper Carts. You will own the roadmap for how our carts see and reason about what’s in the basket, and you’ll build the platforms and models that make checkout seamless in dynamic, real-world retail environments. Your direct team will be ~10 engineers within a broader organization of ~30 spanning Android and hardware.
This is a high-impact role at the frontier of physical AI—bridging edge devices in stores with cloud-scale data and training systems. You’ll partner closely with Android, hardware, product, and operations to deliver measurable improvements in recognition accuracy, latency, and reliability. The role is remote across Canada; West Coast time zones are ideal, but we’re open to great talent anywhere in the country. Learn more about our work at Connecting stores from edge to cloud: reinventing retail with physical AI.
About the Job
- Lead and grow a team of ~10 ML, CV and AI infrastructure engineers building the perception and reasoning systems that power Caper Carts in live retail environments.
- Define the technical vision, roadmap, and success metrics for cart perception and multimodal understanding; prioritize work that drives measurable gains in item recognition accuracy, checkout speed, and system reliability.
- Architect scalable training, data, and inference platforms on GCP using Ray, Kubernetes, and modern MLOps practices to enable rapid experimentation and safe, repeatable deployments.
- Deliver production-grade CV/VLM models for multi-camera item detection, weighing, and basket reasoning; optimize on-device inference for low-latency, high-availability operation at the edge.
- Build the data flywheel end-to-end—instrumentation, labeling, evaluation, offline/online testing, and monitoring—to continuously improve performance across diverse store conditions.
- Collaborate cross-functionally with Android, hardware, product, design, operations, and retailer partners; communicate risks, tradeoffs, and timelines clearly in a fast-paced, ever-evolving environment.
About You
Minimum Qualifications
- 8+ years of experience building and deploying machine learning systems, with a strong focus on computer vision in production environments.
- 2+ years of experience managing teams of 6+ ML/CV/AI engineers, including hiring, performance management, and career development.
- Hands-on expertise with computer vision, deep learning (e.g., PyTorch), model training/evaluation, and MLOps practices for reliable CI/CD of ML services.
- Proven experience architecting and operating ML infrastructure on GCP (e.g., GKE, Vertex AI, BigQuery) and distributed training/inference with Ray; containerization with Docker and orchestration with Kubernetes.
- Experience delivering real-time edge inference, including model optimization (e.g., TensorRT, ONNX, quantization) and monitoring for latency, throughput, and accuracy.
- Proficiency in Python and SQL, with a track record of shipping end-to-end CV systems including data pipelines, experimentation, deployment, and post-launch iteration.
- Bachelor’s degree in Computer Science, Electrical/Computer Engineering, or a related technical field, or equivalent practical experience.
Preferred Qualifications
- Experience integrating on-device ML with Android applications and collaborating closely with Android teams on SDKs and APIs.
- Background with multimodal vision-language models (VLMs) and large language models (LLMs) for perception, retrieval, or instruction-based reasoning.
- Experience with sensors and hardware integration (e.g., multi-camera setups, weight sensors), calibration, and dataset generation for robotics or retail environments.
- Demonstrated success leading cross-functional programs across 3+ partner teams and delivering multi-quarter roadmaps.
- Graduate degree (MS/PhD) in a relevant field with research or applied focus in computer vision, machine learning, or robotics.
LI-Remote
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.
For US based candidates, the base pay ranges for a successful candidate are listed below.
CA, NY, CT, NJ
$240,000 - $253,000 USD
WA
$230,000 - $243,000 USD
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
$221,000 - $233,000 USD
All other states
$201,000 - $212,000 USD
See all 668+ H-1B1 Singapore Visa Machine Learning Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa Machine Learning Manager Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Manager
Verify your degree meets specialty occupation standards
Machine Learning Manager roles require a directly related degree, not just any STEM background. Pull the O*NET profile for this occupation and confirm your degree field maps to the listed education requirements before applying, since mismatches trigger consular questions.
Target employers with existing H-1B1 LCA filings
Search Migrate Mate to find employers who've already filed Labor Condition Applications for H-1B1 Singapore holders. These companies have established DOL compliance workflows, reducing the time between your offer letter and certified LCA.
Request an LCA that covers your managerial scope
Your employer files the LCA with DOL specifying your job duties and wage level. For an ML Manager role, insist the LCA reflects management responsibilities, not just individual contributor duties, or you risk a mismatch during consular review.
Benchmark your offered wage against OFLC Wage Search data
Before signing an offer, run your job title and location through OFLC Wage Search to confirm your salary meets or exceeds the prevailing wage for your SOC code. DOL will deny LCA certification if the offered wage falls short, stalling your entire application.
Prepare NIE documentation if your employer is cap-exempt
If your prospective employer is a university or nonprofit research institution, they may file outside the 5,400 cap entirely. Confirm cap-exempt status with your employer's HR team early, since the consular filing packet differs from standard H-1B1 Singapore applications.
Consolidate your portfolio of ML project outcomes before the interview
Consular officers assess specialty occupation by reviewing your actual work, not just your title. Bring documented evidence of ML models you've shipped, team size you've managed, and measurable business outcomes to substantiate your Manager classification at the interview window.
Frequently Asked Questions
Does a Machine Learning Manager role qualify as a specialty occupation for the H-1B1 Singapore visa?
Yes, provided the role requires at least a bachelor's degree in a directly related field such as computer science, statistics, or a related quantitative discipline. Managerial titles add a layer of scrutiny, so your employer's LCA and your consular packet should document that the management duties themselves require that specialized degree, not just the technical work you oversee.
How does the H-1B1 Singapore visa compare to the H-1B for a Machine Learning Manager?
The H-1B1 Singapore visa skips the H-1B lottery entirely, which means your start date isn't tied to an April selection event. Your employer files a Labor Condition Application with DOL and you apply directly at the U.S. consulate in Singapore. The tradeoff is that H-1B visa1 doesn't confer dual intent, so you can't use it as a stepping stone toward a green card without additional planning.
How do I find employers that actively sponsor H-1B1 Singapore visas for Machine Learning Manager roles?
Migrate Mate filters job listings by employers with verified H-1B1 visa LCA filing history, so you can identify companies that have already navigated the DOL certification process for Singaporean professionals. This saves significant time compared to cold-applying and then discovering an employer has no H-1B1 infrastructure after you've received an offer.
Can my employer file the H-1B1 LCA while I'm still working in Singapore?
Yes, and that's the standard sequence. Your employer certifies the LCA with DOL, then you use the certified LCA along with your offer letter and supporting documents to apply at the U.S. Embassy or Consulate General in Singapore. You don't need to be in the United States or hold any prior U.S. status for the process to begin.
What happens to my H-1B1 status if my Machine Learning Manager role changes significantly after I arrive?
Material changes to your job duties, employer, or work location require your employer to file an amended LCA with DOL reflecting the new conditions. If the role shifts from managing ML teams to primarily individual contributor work, the specialty occupation basis of your status could be challenged at renewal. Your employer's immigration counsel should review any substantial title or scope changes before they take effect.