H-1B Visa Efficiency Engineer Jobs
Efficiency Engineers apply industrial engineering methods to cut waste, reduce cycle times, and improve process performance across manufacturing, logistics, and operations. Employers filing H-1B visa petitions for this role must certify a prevailing wage through DOL and demonstrate the position qualifies as a specialty occupation requiring at least a bachelor's degree in industrial engineering or a closely related field.
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Get Access To All JobsINTRODUCTION
We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!
ROLE AND RESPONSIBILITIES
What You Will Be Doing
- Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings
- Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers
- Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more
- Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure
- Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them
- Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
BASIC QUALIFICATIONS
What We Need To See
- BS or similar background in Computer Science or related area (or equivalent experience)
- Minimum 5+ years of experience designing and operating large scale compute infrastructure
- Strong understanding of modern ML techniques and tools
- Experience investigating, and resolving, training & inference performance end to end
- Debugging and optimization experience with NSight Systems and NSight Compute
- Experience with debugging large-scale distributed training using NCCL
- Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.
- Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
- Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking
- Experience with Machine Learning and Deep Learning concepts, algorithms and models
- Familiarity with InfiniBand with IBOP and RDMA
- Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads
- Familiarity with deep learning frameworks like PyTorch and TensorFlow
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you. 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 March 23, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
JR2013283
INTRODUCTION
We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!
ROLE AND RESPONSIBILITIES
What You Will Be Doing
- Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings
- Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers
- Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more
- Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure
- Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them
- Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
BASIC QUALIFICATIONS
What We Need To See
- BS or similar background in Computer Science or related area (or equivalent experience)
- Minimum 5+ years of experience designing and operating large scale compute infrastructure
- Strong understanding of modern ML techniques and tools
- Experience investigating, and resolving, training & inference performance end to end
- Debugging and optimization experience with NSight Systems and NSight Compute
- Experience with debugging large-scale distributed training using NCCL
- Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.
- Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
- Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking
- Experience with Machine Learning and Deep Learning concepts, algorithms and models
- Familiarity with InfiniBand with IBOP and RDMA
- Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads
- Familiarity with deep learning frameworks like PyTorch and TensorFlow
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you. 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 March 23, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
JR2013283
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an Efficiency Engineer
Confirm your degree supports specialty occupation
USCIS requires a direct relationship between your degree field and the Efficiency Engineer role. A general management or business degree alone often triggers an RFE. Industrial engineering, systems engineering, or operations research degrees create the clearest specialty occupation case.
Check prevailing wage levels before negotiating
Use the OFLC Wage Search to look up wage levels for your target job title and location. Employers must certify at least Level 1. Knowing the threshold before your offer conversation prevents misaligned expectations that stall LCA filing.
Target employers with active LCA filing history
Use Migrate Mate to filter Efficiency Engineer roles by employers who have filed Labor Condition Applications for this occupation. That filing history confirms the employer understands the H-1B process and has sponsored similar roles before.
Verify the role maps to the right O*NET code
Review your O*NET occupation profile for Industrial Engineers before your employer drafts the LCA. If the job description uses vague efficiency titles without referencing engineering methodology, the petition is harder to defend as a specialty occupation at USCIS.
Address employer E-Verify status early in outreach
H-1B employers aren't universally required to use E-Verify unless they're federal contractors or operating in certain states. Confirm your prospective employer's verification status before the offer stage so there are no onboarding delays after your petition is approved.
Plan your timeline around the cap and start date
H-1B cap-subject petitions can only be filed for an October 1 start date after a March registration window. If you're interviewing outside that window, ask whether the employer qualifies as cap-exempt or discuss bridging your status through OPT or another category.
H-1B Visa Efficiency Engineer: Frequently Asked Questions
Does an Efficiency Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, provided the job description requires at least a bachelor's degree in industrial engineering, systems engineering, or operations research. USCIS scrutinizes roles with broad titles, so the employer's job description must tie the duties directly to engineering methodology. Titles like 'Efficiency Analyst' without engineering-specific requirements are harder to defend than roles with explicit process modeling or statistical analysis duties.
What SOC code do employers typically use when filing an H-1B for an Efficiency Engineer?
Most employers file under SOC 17-2112 (Industrial Engineers) or 13-1081 (Logisticians) depending on whether the role is engineering-driven or operations-driven. The SOC code affects which prevailing wage applies in the DOL's OFLC Wage Search, so a misclassified code can result in an incorrectly certified wage that later causes problems at USCIS. Confirm the code matches your actual duties before the LCA is submitted.
How do I find employers who have sponsored H-1B visas for Efficiency Engineer roles before?
Migrate Mate lets you browse Efficiency Engineer jobs filtered by employers with verified H-1B Labor Condition Application history. This is more reliable than relying on a recruiter's assurances, because LCA filings are public DOL records. Employers who have filed for this occupation code before have already cleared the internal approval and legal review steps that often slow down first-time sponsors.
Can my employer start my H-1B petition while I'm on OPT as an Efficiency Engineer?
Yes. If your OPT is still valid when the H-1B cap registration opens in March, your employer files a registration on your behalf. If selected and your OPT expires before October 1, the cap-gap rule extends your work authorization automatically. You can continue working for the same employer throughout the gap period as long as the petition is timely filed and pending with USCIS.
What documents should I prepare before an employer files my H-1B petition as an Efficiency Engineer?
You'll need official transcripts showing your engineering degree, a credential evaluation if your degree is from outside the U.S., copies of your passport and any prior visa documents, and a detailed resume showing engineering-specific duties. If your degree is in a field adjacent to industrial engineering, a professional evaluation letter explaining how your coursework maps to the role significantly reduces the risk of a specialty occupation RFE from USCIS.