Principal Machine Learning Engineer Visa Sponsorship Jobs in North Carolina
Principal machine learning engineer visa sponsorship jobs in North Carolina concentrate in the Research Triangle, where companies like Red Hat, Lenovo, and SAS Institute hire advanced ML talent. Durham, Raleigh, and Charlotte all have active sponsorship histories. North Carolina's university ecosystem and established tech sector support strong demand for senior ML engineering roles.
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Invent the future with us.
Ampere is a semiconductor design company for a new era, leading the future of computing with an innovative approach to CPU design focused on high-performance, energy efficient AI compute.
As a pioneer in the new frontier of energy efficient high-performance computing, Ampere is part of the Softbank Group of companies driving sustainable computing for AI, Cloud, and edge applications.
Join us at Ampere and work alongside a passionate and growing team - we’d love to have you apply!
About the Role
As a Sr. Principal Machine Learning Software Engineer, you will lead the architecture and development of high-performance AI inference-serving software for Ampere accelerators. You will work across model serving, frameworks, compilers, runtimes, and optimized kernels to enable efficient deployment of modern AI workloads, including generative AI and large language models.
This is a hands-on technical leadership role for someone who can solve complex systems and performance challenges while influencing the broader AI software and hardware roadmap.
What You’ll Achieve:
- Architect and build an inference-serving engine that supports and optimizes state-of-the-art AI models on Ampere deep learning accelerators.
- Drive end-to-end serving performance, including throughput, latency, tail latency, memory efficiency, scalability, and cost per inference.
- Develop key serving capabilities such as batching and scheduling, KV-cache management, model loading, memory planning, quantization, and multi-device or distributed inference.
- Collaborate across model-serving, framework, compiler, runtime, kernel, and hardware teams to deliver a cohesive, high-performance AI software stack.
- Optimize model execution through graph compilation, operator fusion, precision optimization, efficient attention, and hardware-specific execution strategies.
- Influence future accelerator architecture through hardware/software co-design, translating real-world AI workload requirements into product recommendations.
- Establish technical direction, design standards, benchmarking practices, and performance-validation processes for the serving platform.
- Evaluate, integrate, and contribute to relevant open-source AI serving and runtime technologies.
- Mentor engineers and lead technical decisions across cross-functional initiatives.
- Partner with product, field, and customer teams to prioritize capabilities and deliver production-ready AI solutions.
About You:
- Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related technical field with 12+ years of relevant experience; master’s degree with 8+ years; or Ph.D. with 5+ years.
- Experience developing or optimizing production inference runtimes, serving engines, deployment toolkits, or high-performance AI systems.
- Experience with technologies such as vLLM, llama.cpp, TensorRT/TensorRT-LLM, ONNX Runtime, OpenVINO, Triton Inference Server, TVM, XLA, MLIR, or comparable systems.
- Expert proficiency in modern C++ and strong experience in C, including concurrent programming, memory management, and systems-level performance optimization.
- Strong understanding of AI inference performance, including batching, scheduling, latency/throughput tradeoffs, memory bandwidth, KV-cache behavior, quantization, and accelerator utilization.
- Experience with profiling, benchmarking, performance analysis, and low-level systems debugging.
- Demonstrated ability to lead complex cross-functional technical initiatives and communicate effectively with software, hardware, and product stakeholders.
Preferred Qualifications
- Experience with LLM, transformer, multimodal, or generative-AI inference.
- Experience with AI frameworks and heterogeneous computing technologies such as PyTorch, oneDNN, SYCL, OpenCL, OpenMP, MPI, CUDA, ROCm, or similar platforms.
- Experience with ML compilers, graph optimization, code generation, kernel development, or device runtimes.
- Familiarity with distributed inference, cloud-native serving, containers, Kubernetes, orchestration, observability, or multi-tenant systems.
- Experience with model optimization techniques, including mixed precision, INT8/INT4/FP8 quantization, sparsity, or efficient-attention methods.
- Experience collaborating with hardware architecture teams on hardware/software co-design.
- Contributions to relevant open-source AI, compiler, runtime, or HPC projects.
What We’ll Offer:
At Ampere we believe in taking care of our employees and providing a competitive total rewards package that includes base pay, cash long-term incentive, and comprehensive benefits. The full base pay range for this role is between $225,500 and $338,500, except in the San Francisco Bay Area where the range is between $237,000 and $356,000.
Our benefits include health, wellness, and financial programs that support employees through every stage of life.
Benefit highlights include:
- Premium medical insurance, dental insurance, vision insurance, as well as income protection and a 401K retirement plan, so that you can feel secure in your health and financial future.
- Unlimited Flextime and 10+ paid holidays so that you can embrace a healthy work-life balance.
- A variety of healthy snacks, energizing espresso, and refreshing drinks to keep you fueled and focused throughout the day.
And there is much more than compensation and benefits. At Ampere, we foster an inclusive culture that empowers our employees to do more and grow more. We are excited to share more about our career opportunities with you through the interview process. Our benefits include health, wellness, and financial programs that support employees through every stage of life.
LI-Hybrid
LI-Hybrid#LI-DR
LI-Hybrid
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Ampere is an inclusive and equal opportunity employer and welcomes applicants from all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, religion, age, veteran and/or military status, sex, sexual orientation, gender, gender identity, gender expression, physical or mental disability, or any other basis protected by federal, state or local law.
Description
Invent the future with us.
Ampere is a semiconductor design company for a new era, leading the future of computing with an innovative approach to CPU design focused on high-performance, energy efficient AI compute.
As a pioneer in the new frontier of energy efficient high-performance computing, Ampere is part of the Softbank Group of companies driving sustainable computing for AI, Cloud, and edge applications.
Join us at Ampere and work alongside a passionate and growing team - we’d love to have you apply!
About the Role
As a Sr. Principal Machine Learning Software Engineer, you will lead the architecture and development of high-performance AI inference-serving software for Ampere accelerators. You will work across model serving, frameworks, compilers, runtimes, and optimized kernels to enable efficient deployment of modern AI workloads, including generative AI and large language models.
This is a hands-on technical leadership role for someone who can solve complex systems and performance challenges while influencing the broader AI software and hardware roadmap.
What You’ll Achieve:
- Architect and build an inference-serving engine that supports and optimizes state-of-the-art AI models on Ampere deep learning accelerators.
- Drive end-to-end serving performance, including throughput, latency, tail latency, memory efficiency, scalability, and cost per inference.
- Develop key serving capabilities such as batching and scheduling, KV-cache management, model loading, memory planning, quantization, and multi-device or distributed inference.
- Collaborate across model-serving, framework, compiler, runtime, kernel, and hardware teams to deliver a cohesive, high-performance AI software stack.
- Optimize model execution through graph compilation, operator fusion, precision optimization, efficient attention, and hardware-specific execution strategies.
- Influence future accelerator architecture through hardware/software co-design, translating real-world AI workload requirements into product recommendations.
- Establish technical direction, design standards, benchmarking practices, and performance-validation processes for the serving platform.
- Evaluate, integrate, and contribute to relevant open-source AI serving and runtime technologies.
- Mentor engineers and lead technical decisions across cross-functional initiatives.
- Partner with product, field, and customer teams to prioritize capabilities and deliver production-ready AI solutions.
About You:
- Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related technical field with 12+ years of relevant experience; master’s degree with 8+ years; or Ph.D. with 5+ years.
- Experience developing or optimizing production inference runtimes, serving engines, deployment toolkits, or high-performance AI systems.
- Experience with technologies such as vLLM, llama.cpp, TensorRT/TensorRT-LLM, ONNX Runtime, OpenVINO, Triton Inference Server, TVM, XLA, MLIR, or comparable systems.
- Expert proficiency in modern C++ and strong experience in C, including concurrent programming, memory management, and systems-level performance optimization.
- Strong understanding of AI inference performance, including batching, scheduling, latency/throughput tradeoffs, memory bandwidth, KV-cache behavior, quantization, and accelerator utilization.
- Experience with profiling, benchmarking, performance analysis, and low-level systems debugging.
- Demonstrated ability to lead complex cross-functional technical initiatives and communicate effectively with software, hardware, and product stakeholders.
Preferred Qualifications
- Experience with LLM, transformer, multimodal, or generative-AI inference.
- Experience with AI frameworks and heterogeneous computing technologies such as PyTorch, oneDNN, SYCL, OpenCL, OpenMP, MPI, CUDA, ROCm, or similar platforms.
- Experience with ML compilers, graph optimization, code generation, kernel development, or device runtimes.
- Familiarity with distributed inference, cloud-native serving, containers, Kubernetes, orchestration, observability, or multi-tenant systems.
- Experience with model optimization techniques, including mixed precision, INT8/INT4/FP8 quantization, sparsity, or efficient-attention methods.
- Experience collaborating with hardware architecture teams on hardware/software co-design.
- Contributions to relevant open-source AI, compiler, runtime, or HPC projects.
What We’ll Offer:
At Ampere we believe in taking care of our employees and providing a competitive total rewards package that includes base pay, cash long-term incentive, and comprehensive benefits. The full base pay range for this role is between $225,500 and $338,500, except in the San Francisco Bay Area where the range is between $237,000 and $356,000.
Our benefits include health, wellness, and financial programs that support employees through every stage of life.
Benefit highlights include:
- Premium medical insurance, dental insurance, vision insurance, as well as income protection and a 401K retirement plan, so that you can feel secure in your health and financial future.
- Unlimited Flextime and 10+ paid holidays so that you can embrace a healthy work-life balance.
- A variety of healthy snacks, energizing espresso, and refreshing drinks to keep you fueled and focused throughout the day.
And there is much more than compensation and benefits. At Ampere, we foster an inclusive culture that empowers our employees to do more and grow more. We are excited to share more about our career opportunities with you through the interview process. Our benefits include health, wellness, and financial programs that support employees through every stage of life.
LI-Hybrid
LI-Hybrid#LI-DR
LI-Hybrid
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Ampere is an inclusive and equal opportunity employer and welcomes applicants from all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, religion, age, veteran and/or military status, sex, sexual orientation, gender, gender identity, gender expression, physical or mental disability, or any other basis protected by federal, state or local law.
Principal Machine Learning Engineer Job Roles in North Carolina
See all Principal Machine Learning Engineer Jobs in North Carolina
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Search Principal Machine Learning Engineer Jobs in North CarolinaPrincipal Machine Learning Engineer Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for principal machine learning engineers in North Carolina?
Technology and enterprise software employers in the Research Triangle are the most active sponsors for principal machine learning engineers in North Carolina. Companies including Red Hat, SAS Institute, Lenovo, Fidelity Investments, and Bandwidth have filed Labor Condition Applications for senior ML engineering roles. Healthcare technology firms in Durham and financial services companies in Charlotte also sponsor this level of position.
Which visa types realistically fit principal machine learning engineer roles in North Carolina?
Principal machine learning engineer roles qualify as specialty occupations, so H-1B visa is the primary path for most international candidates. The H-1B is subject to an annual cap and selection process, so timing matters. Australian citizens can pursue the E-3 visa, which has no lottery. Chilean and Singaporean nationals may use the H-1B1 visa. Canadian and Mexican citizens holding an engineering degree may qualify under the TN visa category. EB-2 and EB-3 green card categories are available for longer-term permanent residence.
How to find principal machine learning engineer visa sponsorship jobs in North Carolina?
Migrate Mate lists North Carolina employers with verified visa sponsorship histories for principal machine learning engineer roles, searchable by city and employer. Because sponsorship activity is concentrated in Research Triangle cities like Raleigh, Durham, and Chapel Hill, filtering by location helps identify the most active hiring companies. Migrate Mate's database draws on employer filing records, so you can see which companies have sponsored senior ML engineering positions rather than relying on job listing claims alone.
Which cities in North Carolina have the most principal machine learning engineer sponsorship jobs?
Raleigh and Durham account for the largest share of principal machine learning engineer sponsorship activity in North Carolina, driven by the Research Triangle Park concentration of technology, biotech, and enterprise software employers. Chapel Hill adds university-adjacent opportunities, particularly with health system and research employers. Charlotte has a growing presence through financial services and fintech companies that sponsor senior ML engineering talent.
Are there state-specific factors that affect visa sponsorship for principal machine learning engineers in North Carolina?
North Carolina's Research Triangle Park is one of the largest research and technology campuses in the country, which concentrates sponsoring employers in a relatively small geographic area. The state's university system, including NC State University and Duke University, creates pipelines of ML talent that employers are accustomed to sponsoring. SAS Institute, headquartered in Cary, is particularly notable as a long-standing sponsor of advanced analytics and machine learning engineering roles at senior levels.
What is the prevailing wage for sponsored principal machine learning engineer jobs in North Carolina?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.