Efficiency Engineer Jobs
Efficiency Engineer jobs are open across manufacturing, logistics, healthcare, and consulting, at levels from entry-level to senior and principal, with specializations in process improvement, lean operations, and industrial systems. Find a role that fits from the openings below and apply directly.
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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
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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Find Efficiency Engineer JobsEfficiency Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple5
- Resource Innovations5
- Fastly4
- NVIDIA3
- Nuro2
Top Industries Hiring
- Technology & Software11
- Consulting & Professional Services6
- Banking & Financial Services4
- Electronics & Hardware3
- Automotive2
What Employers Look For
The qualifications that appear most often in efficiency engineer jobs.
- Bachelor's degree in industrial, mechanical, or systems engineering or a closely related field
- Demonstrated experience applying lean manufacturing or Six Sigma methodologies in a production or operations environment
- Proficiency with data analysis tools such as Minitab, Excel, or process simulation software
- Lean Six Sigma Green Belt or Black Belt certification from a recognized credentialing body
- Hands-on experience conducting value stream mapping and leading Kaizen events
- Familiarity with ERP or MES systems used to monitor and manage production workflow data
Tips for Your Efficiency Engineer Job Search
Quantify your process improvement results
Efficiency engineer resumes that convert list measurable outcomes, not responsibilities. Replace vague phrases with numbers: cycle time cut by a specific percentage, throughput increased by a defined amount, or headcount reduced through automation. Hiring managers screen for proof, not potential.
List your lean and Six Sigma credentials
Lean Six Sigma belts, Kaizen facilitation experience, and value stream mapping are screened in applicant tracking systems before a human reads your resume. Place certifications in a dedicated section near the top so they're never buried or missed in the first pass.
Target openings by industry, not just title
Efficiency engineer roles in healthcare operations differ sharply from those in manufacturing or supply chain. Filter your search by industry vertical and read each posting carefully for domain-specific tools like ERP systems, MES platforms, or clinical workflow software before you apply.
Apply early to roles that fit
Migrate Mate lists efficiency engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a case study for your interview
Expect at least one structured problem-solving exercise during your interview. Walk in ready to present a real improvement project using a clear before-and-after framing: the baseline state, the root cause analysis method you used, the changes implemented, and the measurable outcome achieved.
Negotiate using total compensation, not base alone
Efficiency engineer offers often include project bonuses, performance incentives, or profit-sharing tied to measurable cost savings you generate. Before you respond to an offer, understand the full structure so you can negotiate components beyond base salary, including scope of role and project budget authority.
Efficiency Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most efficiency engineers?
The companies hiring the most efficiency engineers right now include Apple, Resource Innovations, and Fastly, with the largest share of openings in California, Michigan, and Texas, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in manufacturing, healthcare systems, and large logistics operations.
How many efficiency engineer jobs are remote?
About 36% of efficiency engineer openings are fully remote or hybrid as of June 2026, though the role is more often on-site than many engineering disciplines. Sub-areas involving data analysis, process documentation, and continuous improvement program management are most likely to offer remote or hybrid flexibility compared to roles requiring direct floor observation.
How do you become an efficiency engineer?
Start with an engineering or operations-related bachelor's degree, then build hands-on experience in a production, logistics, or healthcare environment where you can practice identifying waste and running improvement projects. Earn a Lean Six Sigma Green Belt to validate your methodology skills. From there, lead Kaizen events and document measurable outcomes to build a case study portfolio that distinguishes you in the job market.
Can you get hired as an efficiency engineer with little or no experience?
Yes, entry-level efficiency engineer roles exist, particularly in manufacturing and supply chain companies that run formal rotational or co-op programs. Your best path without direct experience is to complete an internship or co-op that involves process analysis, pursue a Lean Six Sigma Yellow or Green Belt certification independently, and document any school or volunteer project where you identified inefficiency and implemented a change with a measurable result.
What does the efficiency engineer interview process look like?
Most efficiency engineer hiring processes include an initial phone screen with a recruiter, followed by a technical interview covering lean tools, root cause analysis, and data interpretation. A structured case study or take-home problem is common at mid-process, where you're asked to analyze a scenario and propose an improvement plan. Final rounds typically involve presenting your solution to a panel that includes operations leadership and sometimes frontline supervisors.
Where can I find and apply to efficiency engineer jobs?
You can find and apply to efficiency engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Find roles that match your experience and specialization, then apply directly to each listing from the page.
See All Efficiency Engineer Jobs
Jump back to the full list of openings and apply to any efficiency engineer role that fits.
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