TN Visa Efficiency Engineer Jobs
Efficiency Engineer roles qualify for TN visa sponsorship under the USMCA's Industrial Engineer category, making this one of the cleaner paths for Canadian and Mexican professionals to work in the U.S. without a lottery. Employers file no I-129 for Canadians at the port of entry, and most approvals happen same-day.
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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 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
- 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 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 TN Visa Sponsorship as an Efficiency Engineer
Frame your credentials around industrial engineering
TN classification for Efficiency Engineers falls under the Industrial Engineer category. Gather transcripts and degree certificates that explicitly name industrial, manufacturing, or systems engineering, a general engineering degree without that specialization creates unnecessary friction at the border.
Target manufacturers with lean programs already running
Companies that already run Six Sigma or lean manufacturing programs understand what an Efficiency Engineer does and are likelier to recognize TN eligibility. Look for postings that mention kaizen, value stream mapping, or OEE targets, these employers won't need educating on sponsorship.
Use Migrate Mate to filter for TN-ready employers
Search Migrate Mate to find Efficiency Engineer openings at companies with recent visa filings and sponsorship experience. This helps you identify employers who understand work visa processes and are more likely to support your TN application at the port of entry or consulate.
Get the employer support letter right before crossing
Canadian citizens apply directly at the port of entry, so the employer support letter is your primary document. Confirm it specifies your job title as Industrial Engineer, lists your degree field, and names the business purpose, vague letters are the leading cause of TN delays at the border.
Clarify the Mexican TN process with your employer early
Mexican nationals require a visa stamp from a U.S. consulate rather than port-of-entry admission. Tell your employer this upfront so they don't assume the same same-day process Canadians use. Your employer will need to prepare a support letter that documents your job offer and role qualifications, which you'll present at your consulate appointment.
Negotiate the filing timeline into your start date
Canadians can typically start within days of a border crossing, but Mexican nationals need consulate appointment lead time that can stretch several weeks. Build that window into your offer negotiation so your agreed start date is realistic and you don't forfeit the role waiting on paperwork.
Efficiency Engineer jobs are hiring across the US. Find yours.
Find Efficiency Engineer JobsEfficiency Engineer TN Visa: Frequently Asked Questions
Does an Efficiency Engineer role qualify for TN visa status?
Yes, provided the role is classified under the Industrial Engineer category listed in the USMCA schedule. The job duties must involve analyzing and improving production processes, workflows, or operational systems. Titles like Efficiency Engineer, Process Engineer, or Industrial Engineer all commonly qualify, but the offer letter and employer support documentation should reflect those duties clearly.
How does TN compare to H-1B for Efficiency Engineers?
TN has no annual cap or lottery for Canadians, so you can apply any time of year and receive a decision at the port of entry, often the same day. H-1B requires lottery selection and takes months to process. The tradeoff is that TN is tied to your employer and doesn't carry dual-intent protection, but for Efficiency Engineers with a qualifying offer, TN is the faster and more predictable route.
What documents does my employer need to provide for TN sponsorship?
Your employer needs to produce a support letter on company letterhead that specifies your job title, a description of duties consistent with efficiency engineering, your degree qualifications, and the intended duration of employment. For Mexican nationals, you'll apply at a U.S. consulate with this support letter as your primary documentation. Canadian applicants can present the support letter directly at a U.S. port of entry. Neither process involves advance government filings with USCIS or other federal agencies.
How do I find Efficiency Engineer jobs where employers already understand TN sponsorship?
Use Migrate Mate to search for Efficiency Engineer roles filtered by TN visa sponsorship history. Many employers are unfamiliar with TN mechanics, which creates delays even when they're willing to hire. Focusing your search on companies that have sponsored TN workers before reduces the time spent educating HR and moves you to an offer faster.
Can I switch Efficiency Engineer employers after getting TN status?
Yes, but you need a new TN authorization tied to the new employer before you start. Your existing TN status is employer-specific and doesn't transfer. Canadian nationals can get a new TN at the port of entry with documentation from the new employer. Mexican nationals need to return to a U.S. consulate. Plan the transition carefully to avoid any gap in authorized status.
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