H-1B Visa Integration Engineer Jobs
Integration Engineer roles qualify for H-1B visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, software engineering, or a related field. Employers file an LCA with DOL before petitioning USCIS, and the 85,000-cap lottery runs each April for October 1 start dates.
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Get Access To All JobsINTRODUCTION
Intelligent machines powered by artificial intelligence are transforming transportation. NVIDIA is building the computing platforms, software, and AI systems that enable autonomous vehicles to perceive, reason, and act in complex environments. Our team develops NVIDIA’s end-to-end autonomous driving application. We are looking for a Senior Integration Engineer to accelerate the development, integration, evaluation, and deployment of end-to-end driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms. In this role, you will work across model development, data, simulation, systems software, and vehicle engineering. You will help turn rapidly evolving AI models into reliable, high-performance autonomous driving functionality running on NVIDIA’s heterogeneous computing platforms.
ROLE AND RESPONSIBILITIES:
- Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and other autonomous driving components.
- Establish clear model input, output, timing, state-management, and runtime interface contracts.
- Partner with model developers to improve model quality, debuggability, runtime behavior, and readiness for deployment.
- Investigate discrepancies between model behavior in development environments and on target vehicle platforms.
- Optimize model inference and surrounding software to meet latency, throughput, memory, determinism, and power requirements.
- Develop tools and metrics for evaluating driving quality, safety, robustness, and regression performance at scale.
- Perform in-vehicle testing, collect and analyze driving data, and complete autonomous driving missions.
- Develop high-quality production code in C++ and Python using CUDA and other GPU-accelerated technologies.
BASIC QUALIFICATIONS:
- PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, Robotics, Machine Learning, or a related field.
- Strong C++ programming, software architecture, debugging, and performance-analysis skills, and model inference technologies such as CUDA and TensorRT.
- Proficiency in Python and experience working with modern machine-learning frameworks such as PyTorch.
- Experience developing software on Linux and embedded or real-time operating systems such as QNX.
- Experience integrating machine-learning models into complex, performance-sensitive production systems.
- Ability to diagnose issues across model behavior, application software, middleware, operating systems, and hardware.
- Experience with autonomous driving, robotics, ADAS, or another real-time intelligent system.
PREFERRED QUALIFICATIONS:
- Experience deploying end-to-end driving, robotics, or embodied-AI models on production hardware.
- Familiarity with model optimization, quantization, compilation, profiling, and hardware-aware neural-network design.
- A track record of turning research models into robust, measurable, and maintainable product functionality.
- Self-motivation, sound engineering judgment, and a passion for solving cross-functional integration challenges.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 22, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
INTRODUCTION
Intelligent machines powered by artificial intelligence are transforming transportation. NVIDIA is building the computing platforms, software, and AI systems that enable autonomous vehicles to perceive, reason, and act in complex environments. Our team develops NVIDIA’s end-to-end autonomous driving application. We are looking for a Senior Integration Engineer to accelerate the development, integration, evaluation, and deployment of end-to-end driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms. In this role, you will work across model development, data, simulation, systems software, and vehicle engineering. You will help turn rapidly evolving AI models into reliable, high-performance autonomous driving functionality running on NVIDIA’s heterogeneous computing platforms.
ROLE AND RESPONSIBILITIES:
- Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and other autonomous driving components.
- Establish clear model input, output, timing, state-management, and runtime interface contracts.
- Partner with model developers to improve model quality, debuggability, runtime behavior, and readiness for deployment.
- Investigate discrepancies between model behavior in development environments and on target vehicle platforms.
- Optimize model inference and surrounding software to meet latency, throughput, memory, determinism, and power requirements.
- Develop tools and metrics for evaluating driving quality, safety, robustness, and regression performance at scale.
- Perform in-vehicle testing, collect and analyze driving data, and complete autonomous driving missions.
- Develop high-quality production code in C++ and Python using CUDA and other GPU-accelerated technologies.
BASIC QUALIFICATIONS:
- PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, Robotics, Machine Learning, or a related field.
- Strong C++ programming, software architecture, debugging, and performance-analysis skills, and model inference technologies such as CUDA and TensorRT.
- Proficiency in Python and experience working with modern machine-learning frameworks such as PyTorch.
- Experience developing software on Linux and embedded or real-time operating systems such as QNX.
- Experience integrating machine-learning models into complex, performance-sensitive production systems.
- Ability to diagnose issues across model behavior, application software, middleware, operating systems, and hardware.
- Experience with autonomous driving, robotics, ADAS, or another real-time intelligent system.
PREFERRED QUALIFICATIONS:
- Experience deploying end-to-end driving, robotics, or embodied-AI models on production hardware.
- Familiarity with model optimization, quantization, compilation, profiling, and hardware-aware neural-network design.
- A track record of turning research models into robust, measurable, and maintainable product functionality.
- Self-motivation, sound engineering judgment, and a passion for solving cross-functional integration challenges.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 22, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
See all 801+ H-1B Visa Integration Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an Integration Engineer
Map your degree to SOC codes
Integration Engineer roles can fall under multiple SOC codes depending on the employer's LCA filing. Pull your target companies' LCA disclosures through OFLC and confirm which code they use before applying, so your degree field aligns cleanly.
Check prevailing wage before negotiating
Run your target job title and location through the OFLC Wage Search before salary talks. Your employer's LCA must certify wages at or above the prevailing wage level, so knowing Levels I through IV shapes what offer terms are actually viable.
Target cap-exempt employers strategically
Universities, nonprofit research organizations, and government research institutions are cap-exempt. If you miss the lottery, an integration role at one of these employers lets you get H-1B status outside the April cap season entirely.
Verify your employer uses E-Verify
STEM OPT employers must be enrolled in E-Verify. If you're on a STEM OPT extension bridging to H-1B, confirm your employer's active enrollment before your extension start date to avoid a gap in work authorization.
Search H-1B sponsors on Migrate Mate
Filter Integration Engineer roles by employers with active H-1B LCA filing history on Migrate Mate. This surfaces companies already set up to sponsor, cutting out the back-and-forth of asking each employer whether they'll petition USCIS.
File premium processing if timelines are tight
If your OPT or cap-gap period ends close to your petition adjudication window, ask your employer to file Form I-907 for premium processing. USCIS adjudicates premium petitions within 15 business days, reducing the risk of a status gap at job start.
H-1B Visa Integration Engineer: Frequently Asked Questions
Does an Integration Engineer role qualify as a specialty occupation for H-1B?
Yes, Integration Engineer positions typically qualify because they require theoretical and practical application of highly specialized knowledge, and employers generally require at least a bachelor's degree in computer science, software engineering, systems engineering, or a directly related field. Your employer will document the degree requirement in the LCA and H-1B petition. Roles that accept any bachelor's degree, regardless of field, carry more RFE risk, so the job description's degree language matters.
Which employers commonly sponsor H-1B visas for Integration Engineers?
Employers that build or operate complex software ecosystems, including enterprise software vendors, cloud infrastructure companies, financial institutions, and large healthcare systems, file H-1B LCAs for Integration Engineer roles regularly. You can browse verified sponsors filtered by this job title on Migrate Mate, which surfaces employers based on actual DOL LCA filing history rather than self-reported sponsorship policies.
Can I transfer my H-1B to a new Integration Engineer role mid-year?
Yes. H-1B portability under AC21 lets you start working for a new employer as soon as your transfer petition is filed, as long as your previous H-1B was approved and you've been in valid H-1B status. The new employer files a new I-129 petition, and your authorized stay continues during adjudication. The role at the new employer must still qualify as a specialty occupation, so the job description and degree requirements should mirror what USCIS expects for Integration Engineer positions.
What wage level should I expect on an H-1B LCA for an Integration Engineer?
Most mid-level Integration Engineer roles are certified at Level II or Level III under the DOL prevailing wage system. Level I applies to entry-level positions with close supervision, while Level III reflects experienced professionals working independently. You can verify the prevailing wage for your specific job title and work location using the OFLC Wage Search before your offer stage, which tells you the floor your employer must certify.
Does O*NET classify Integration Engineer as a distinct occupation?
O*NET doesn't list Integration Engineer as a standalone occupation. Depending on the role's duties, it typically maps to Software Developers, Systems Software or Computer Systems Engineers and Architects. The SOC code your employer selects on the LCA affects the prevailing wage tier and the USCIS specialty occupation analysis, so it's worth reviewing O*NET job zone classifications for whichever code your employer plans to use before the petition is filed.