H-1B Visa Principal Machine Learning Engineer Jobs
Principal Machine Learning Engineer jobs attract strong H-1B visa sponsorship because the role qualifies as a specialty occupation, requiring at least a bachelor's degree in computer science, statistics, or a directly related field. Employers file an LCA with DOL and an I-129 with USCIS, granting up to three years of initial H-1B visa status.
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Re-architecting Engineering for the Age of Intelligence
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
Who We're Looking For
As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and work directly with customers (often side by side on-site) to embed cutting-edge AI models into tools that are useful and used. For this role, that means manufacturing and maintenance, repair and overhaul (MRO). You have put ML into production on industrial process or sensor data, not benchmarks. You know the difference between a model that scores well offline and one a process owner will accept on a qualified production line. Your data comes off equipment rather than out of a solver: it is sparse, drifting, miscalibrated and partly unrecorded, and you know how to work with it. You've shipped ML systems end to end and at scale: you design, build and test reliable, scalable ML data pipelines, select the right libraries, frameworks and tools, and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready not only to execute but to lead and mentor others.
This Role
You'll work closely with Data Scientists, Simulation Engineers, Manufacturing Process Experts and customers to define the process and physics problems we are solving, and you'll drive decisions on reliable deployment with measurable outcomes on the shop floor.
You'll
- Own the ML approach to manufacturing and MRO data, from modelling through deployment in customer production environments (cloud, on-prem and edge).
- Build production ML on sparse, drifting, miscalibrated process and sensor data (process logs, sensor traces, inspection records, small DoE sets), and judge whether the data is enough to train on.
- Choose between physics simulation, reduced-order and learned models, and fuse simulation with shop-floor measurement where the two disagree.
- Set the UQ and validation standard for what a process recommendation may claim against a qualified process window, and design experiments where machine time is the cost.
- Make models transfer across machines, material lots and consumable batches.
- Define the product requirements that manufacturing and MRO place on the PhysicsX platform.
- Lead scoping and architecture for data and ML systems, and communicate results and trade-offs to senior stakeholders and process owners.
- Build end-to-end training and inference pipelines and APIs (Python, PyTorch, Pandas, FastAPI, SciPy, Kubeflow, among others), including for 3D point-cloud and mesh data, and mentor engineers and data scientists.
- Travel to customer sites worldwide, on average 3-4 weeks per quarter, and take part in scoping new projects and bringing new customers to PhysicsX.
What you've done
We hire on what you've done, so strong candidates can point to things like:
- Built and deployed ML on manufacturing process data (parameter logs, sensor traces, inspection records or small DoE sets) and can say what changed in production as a result.
- Fused simulation output with shop-floor measurement where the two disagreed.
- Set UQ and validation standards that other teams followed.
- Shaped a product or tooling roadmap based on what a site or company actually needed.
- Had a recommendation rejected by a process owner, and understood why.
Experience in aerospace or another regulated manufacturing environment is a plus. It is not required, because the must-have bar can be met in any sector where data comes off equipment.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
What We Offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn’t stop there …
🚀 Equity options - share meaningfully in the company you’re helping to build.
💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.
🍽️ Free team lunch 1x/week - good food, great company, and space to connect.
🏥 Private health insurance – comprehensive cover for you, offering total peace of mind.
👶 Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
📈 Personal development – dedicated support for learning, development, and leveling up over time.
💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.
💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.
🔎 Watch this space, we’re continuing to build this as we grow…
Salary Range
$140,000 - $190,000 depending on experience. Seniority will be assessed throughout our interview process.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
About us
Re-architecting Engineering for the Age of Intelligence
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
Who We're Looking For
As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and work directly with customers (often side by side on-site) to embed cutting-edge AI models into tools that are useful and used. For this role, that means manufacturing and maintenance, repair and overhaul (MRO). You have put ML into production on industrial process or sensor data, not benchmarks. You know the difference between a model that scores well offline and one a process owner will accept on a qualified production line. Your data comes off equipment rather than out of a solver: it is sparse, drifting, miscalibrated and partly unrecorded, and you know how to work with it. You've shipped ML systems end to end and at scale: you design, build and test reliable, scalable ML data pipelines, select the right libraries, frameworks and tools, and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready not only to execute but to lead and mentor others.
This Role
You'll work closely with Data Scientists, Simulation Engineers, Manufacturing Process Experts and customers to define the process and physics problems we are solving, and you'll drive decisions on reliable deployment with measurable outcomes on the shop floor.
You'll
- Own the ML approach to manufacturing and MRO data, from modelling through deployment in customer production environments (cloud, on-prem and edge).
- Build production ML on sparse, drifting, miscalibrated process and sensor data (process logs, sensor traces, inspection records, small DoE sets), and judge whether the data is enough to train on.
- Choose between physics simulation, reduced-order and learned models, and fuse simulation with shop-floor measurement where the two disagree.
- Set the UQ and validation standard for what a process recommendation may claim against a qualified process window, and design experiments where machine time is the cost.
- Make models transfer across machines, material lots and consumable batches.
- Define the product requirements that manufacturing and MRO place on the PhysicsX platform.
- Lead scoping and architecture for data and ML systems, and communicate results and trade-offs to senior stakeholders and process owners.
- Build end-to-end training and inference pipelines and APIs (Python, PyTorch, Pandas, FastAPI, SciPy, Kubeflow, among others), including for 3D point-cloud and mesh data, and mentor engineers and data scientists.
- Travel to customer sites worldwide, on average 3-4 weeks per quarter, and take part in scoping new projects and bringing new customers to PhysicsX.
What you've done
We hire on what you've done, so strong candidates can point to things like:
- Built and deployed ML on manufacturing process data (parameter logs, sensor traces, inspection records or small DoE sets) and can say what changed in production as a result.
- Fused simulation output with shop-floor measurement where the two disagreed.
- Set UQ and validation standards that other teams followed.
- Shaped a product or tooling roadmap based on what a site or company actually needed.
- Had a recommendation rejected by a process owner, and understood why.
Experience in aerospace or another regulated manufacturing environment is a plus. It is not required, because the must-have bar can be met in any sector where data comes off equipment.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
What We Offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn’t stop there …
🚀 Equity options - share meaningfully in the company you’re helping to build.
💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.
🍽️ Free team lunch 1x/week - good food, great company, and space to connect.
🏥 Private health insurance – comprehensive cover for you, offering total peace of mind.
👶 Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
📈 Personal development – dedicated support for learning, development, and leveling up over time.
💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.
💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.
🔎 Watch this space, we’re continuing to build this as we grow…
Salary Range
$140,000 - $190,000 depending on experience. Seniority will be assessed throughout our interview process.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
See all 469+ H-1B Visa Principal Machine Learning Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Principal Machine Learning Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Principal Machine Learning Engineer
Align your credentials to specialty occupation standards
Pull the O*NET profile for Machine Learning Engineers and map your degree field directly to the listed knowledge domains. USCIS scrutinizes whether your specific degree, not just any technical degree, corresponds to the duties of a Principal-level ML role.
Target employers with dedicated ML infrastructure teams
Companies running production ML systems at scale, not just research prototypes, have established H-1B filing workflows and in-house immigration counsel. Search Migrate Mate to find employers with verified H-1B LCA sponsorship history for machine learning roles.
Verify prevailing wage tier before accepting an offer
Principal ML Engineer roles typically fall at DOL wage Level III or IV. Run your offered title and worksite zip code through the OFLC Wage Search before signing anything. An offer below the certified prevailing wage will block LCA approval regardless of your qualifications.
Confirm each worksite has its own certified LCA
If you'll work across multiple offices or client sites, each distinct worksite location requires a separately certified LCA. Raise this with your employer during offer negotiation so the filing timeline accounts for multiple DOL submissions before your start date.
Prepare for specialty occupation RFEs with role documentation
USCIS increasingly issues Requests for Evidence on ML roles where job descriptions include general software duties. Ask your employer to draft an I-129 support letter that ties every listed duty to degree-level machine learning theory, not just programming tasks any engineer could perform.
Track cap-subject deadlines if you're not already in H-1B status
If you're transitioning from OPT or another visa, the H-1B cap applies and selection rules have changed recently. File your registration early in the annual window and line up employer counsel immediately after selection, since the LCA must be certified before the I-129 can be submitted to USCIS.
H-1B Visa Principal Machine Learning Engineer: Frequently Asked Questions
Does a Principal Machine Learning Engineer role qualify as an H-1B specialty occupation?
Yes. The role typically qualifies because it requires at minimum a bachelor's degree in computer science, statistics, applied mathematics, or a closely related field. The position involves advanced model development, system architecture, and research-level problem-solving that directly maps to that degree requirement. USCIS evaluates the actual duties listed in the job description, so employers should ensure the posting reflects degree-level ML responsibilities throughout.
How do I find employers actively sponsoring H-1B visas for ML engineering roles?
Browse Migrate Mate to search employers with verified H-1B LCA sponsorship history for machine learning and software engineering positions. Because LCA filings are public DOL records, Migrate Mate surfaces which companies have actually sponsored these roles, letting you prioritize outreach toward employers with established immigration filing processes rather than guessing from job boards.
What happens to my H-1B status if my employer is acquired or restructures?
A corporate acquisition using a stock purchase generally allows H-1B status to continue if the employer-employee relationship and job duties remain unchanged. An asset purchase or significant restructuring may require a new I-129 petition. Notify your immigration counsel as soon as a merger is announced, and confirm whether a successor-in-interest filing applies to your situation under USCIS successor employer guidance.
Can I work remotely from a different state than my original LCA worksite?
No. Each worksite requires its own certified LCA listing the specific location and applicable prevailing wage for that area. If you relocate or regularly work from a home office in a different metropolitan area, your employer must file a new LCA for that location before you begin working there. Failing to do so puts both your status and your employer's compliance record at risk.
How long does H-1B status last for a Principal Machine Learning Engineer?
Initial H-1B status is granted for up to three years, with the option to extend for another three years, reaching a six-year maximum under standard rules. Beyond that, extensions are possible if you have an approved I-140 immigrant petition or a PERM labor certification that has been pending for a qualifying period, allowing you to remain in H-1B status while your green card case progresses.