Efficiency Engineer Jobs in USA with Visa Sponsorship
Efficiency engineers optimize manufacturing processes, supply chains, and operational workflows to reduce waste and improve productivity. Most positions qualify for H-1B sponsorship as specialty occupations requiring industrial engineering, operations research, or related degrees. Companies frequently sponsor efficiency engineers due to their direct impact on cost reduction and operational performance. For detailed occupation requirements, see the O*NET profile.
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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
- 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
- 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
- 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 February 24, 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
- 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
- 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
- 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 February 24, 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
How to Get Visa Sponsorship as an Efficiency Engineer
Highlight quantified process improvements
Document specific efficiency gains you've achieved, like reducing production time by 15% or cutting material waste by $200K annually. Employers value measurable operational impact when justifying visa sponsorship costs.
Target manufacturing and logistics companies
Focus on manufacturers, distribution centers, and supply chain companies with complex operations. These employers regularly sponsor efficiency engineers because process optimization directly affects their bottom line and competitiveness.
Emphasize Lean Six Sigma certifications
Green Belt or Black Belt certifications strengthen your specialty occupation case. These credentials demonstrate specialized knowledge in process improvement methodologies that require formal training beyond general business skills.
Show cross-functional project experience
Highlight projects where you worked with engineering, operations, and finance teams. This demonstrates the specialized coordination skills that distinguish efficiency engineering from general management or analyst roles.
Connect degree to specific methodologies
Explain how your industrial engineering, operations research, or systems engineering degree directly relates to efficiency analysis techniques like statistical process control, operations research, or systems optimization you'll use.
Research company's operational challenges
Before interviews, study the company's recent efficiency initiatives, automation projects, or operational pain points mentioned in earnings calls. Show how your skills address their specific improvement needs.
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Get Access To All JobsFrequently Asked Questions
Do efficiency engineers qualify for H-1B visa sponsorship?
Yes, efficiency engineer positions typically qualify for H-1B sponsorship as specialty occupations. The role requires specialized knowledge in industrial engineering principles, process optimization, statistical analysis, and operations research that directly relates to engineering or related degree requirements. Most efficiency engineering jobs require at least a bachelor's degree in industrial engineering, operations research, or related field.
What degree do I need for efficiency engineer visa sponsorship?
Most efficiency engineer positions require a bachelor's degree in industrial engineering, operations research, systems engineering, or manufacturing engineering. Some employers also accept mechanical engineering, business with operations focus, or supply chain management degrees if combined with relevant process improvement experience. The degree requirement helps establish the specialty occupation classification needed for H-1B approval.
Which companies sponsor efficiency engineers for work visas?
Manufacturing companies, automotive manufacturers, aerospace firms, food and beverage producers, pharmaceutical companies, and logistics providers frequently sponsor efficiency engineers. Companies like Boeing, General Motors, Procter & Gamble, Amazon fulfillment centers, and medical device manufacturers regularly hire efficiency engineers on H-1B visas because process optimization directly impacts their operational costs and productivity.
Are efficiency engineer H-1B applications often approved?
Efficiency engineer H-1B petitions generally have good approval rates when properly documented. The key is demonstrating that the role requires specialized engineering knowledge rather than general business analysis skills. Strong petitions emphasize statistical process control, operations research methodologies, industrial engineering principles, and complex system optimization that require formal engineering education beyond basic business or management training.
Can efficiency engineers get green cards through employment?
Yes, efficiency engineers can pursue employment-based green cards, typically through EB-2 or EB-3 categories. Those with advanced degrees or exceptional ability in process optimization may qualify for EB-2, while others use EB-3. The PERM labor certification process is often successful for efficiency engineers because the role requires specialized skills that are difficult to find among U.S. workers.
What is the prevailing wage requirement for sponsored Efficiency Engineer jobs?
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.
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