H-1B Visa Performance Engineer Jobs
Performance Engineers optimize application speed, scalability, and reliability under load, skills that map cleanly to H-1B visa specialty occupation requirements. Most roles fall under SOC codes tied to software development or systems engineering, making LCA filing and prevailing wage certification straightforward for experienced sponsors.
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Get Access To All JobsAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.
You Might Be a Good Fit If You
- Have deep experience with GPU programming and optimization at scale
- Are impact-driven, passionate about delivering measurable performance breakthroughs
- Can navigate complex systems from hardware interfaces to high-level ML frameworks
- Enjoy collaborative problem-solving and pair programming
- Want to work on state-of-the-art language models with real-world impact
- Care about the societal impacts of your work
- Thrive in ambiguous environments where you define the path forward
Strong Candidates May Also Have Experience With
- GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization
- ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators
- Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight
- Distributed Systems: NCCL, NVLink, collective communication, model parallelism
- Low-Precision: INT8/FP8 quantization, mixed-precision techniques
- Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration
Representative Projects
- Co-design attention mechanisms and algorithms for next-generation hardware architectures
- Develop custom kernels for emerging quantization formats and mixed-precision techniques
- Design distributed communication strategies for multi-node GPU clusters
- Optimize end-to-end training and inference pipelines for frontier language models
- Build performance modeling frameworks to predict and optimize GPU utilization
- Implement kernel fusion strategies to minimize memory bandwidth bottlenecks
- Create resilient systems for planet-scale distributed training infrastructure
- Profile and eliminate performance bottlenecks in production serving infrastructure
- Partner with hardware vendors to influence future accelerator capabilities and software stacks
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The Expected Salary Range For This Position Is
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$280,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.
You Might Be a Good Fit If You
- Have deep experience with GPU programming and optimization at scale
- Are impact-driven, passionate about delivering measurable performance breakthroughs
- Can navigate complex systems from hardware interfaces to high-level ML frameworks
- Enjoy collaborative problem-solving and pair programming
- Want to work on state-of-the-art language models with real-world impact
- Care about the societal impacts of your work
- Thrive in ambiguous environments where you define the path forward
Strong Candidates May Also Have Experience With
- GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization
- ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators
- Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight
- Distributed Systems: NCCL, NVLink, collective communication, model parallelism
- Low-Precision: INT8/FP8 quantization, mixed-precision techniques
- Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration
Representative Projects
- Co-design attention mechanisms and algorithms for next-generation hardware architectures
- Develop custom kernels for emerging quantization formats and mixed-precision techniques
- Design distributed communication strategies for multi-node GPU clusters
- Optimize end-to-end training and inference pipelines for frontier language models
- Build performance modeling frameworks to predict and optimize GPU utilization
- Implement kernel fusion strategies to minimize memory bandwidth bottlenecks
- Create resilient systems for planet-scale distributed training infrastructure
- Profile and eliminate performance bottlenecks in production serving infrastructure
- Partner with hardware vendors to influence future accelerator capabilities and software stacks
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The Expected Salary Range For This Position Is
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$280,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about our policy for using AI in our application process.
See all 395+ H-1B Visa Performance Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Performance Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Performance Engineer
Match your SOC code before applying
Performance Engineer roles get filed under different SOC codes depending on scope. Check the O*NET to confirm whether your work aligns with software developers, systems engineers, or a related classification before your employer files the LCA.
Target employers with load testing infrastructure
Companies running high-traffic platforms, SaaS products, or distributed systems sponsor H-1B Performance Engineers most consistently. Filter on Migrate Mate by LCA filing history to find employers who've sponsored this role before.
Verify your prevailing wage tier early
Run an OFLC Wage Search using your target SOC code and work location before negotiating an offer. Wage Level II or III is typical for mid-senior Performance Engineers, and your offered salary must meet or exceed the certified level.
Document tool-specific expertise on your resume
USCIS requires evidence that the role is a specialty occupation. Listing specific profilers, load testing frameworks, and observability platforms you've used strengthens the employer's petition by tying your degree field directly to the technical duties.
Clarify remote work terms before LCA filing
If you'll work remotely or across multiple offices, your employer must file a separate LCA or amend the existing one for each worksite. Confirm the work location structure with HR before the LCA is submitted to DOL to avoid costly amendments.
Time your start date against cap-gap carefully
If you're on OPT and selected in the H-1B lottery, your cap-gap protection runs through September 30. Negotiate an October 1 start date with your employer so your authorization is uninterrupted when the new fiscal year begins.
H-1B Visa Performance Engineer: Frequently Asked Questions
Does a Performance Engineer role qualify as an H-1B specialty occupation?
Yes. Performance Engineering requires at least a bachelor's degree in computer science, software engineering, or a closely related field, which satisfies the USCIS specialty occupation standard. Roles focused on load testing, capacity planning, and system profiling have a well-established filing history under software development and systems engineering SOC codes.
Which employers sponsor H-1B visas for Performance Engineers?
Technology companies, financial services firms, and large e-commerce platforms hire Performance Engineers with H-1B sponsorship most frequently. These employers run high-traffic systems that require dedicated performance work year-round. You can search Migrate Mate to find companies with verified LCA filing history for this role type, filtered by location and industry.
How does the prevailing wage requirement affect Performance Engineer offers?
Your employer's offered salary must meet the prevailing wage for your SOC code and work location, as certified by DOL on the LCA. Performance Engineers at mid-senior levels typically fall at Wage Level II or III. You can check the applicable wage floor using the OFLC Wage Search before you receive or evaluate a formal offer.
Can a Performance Engineer role support H-1B transfer to a new employer?
Yes. H-1B portability under AC21 lets you start working for a new employer as soon as they file an H-1B transfer petition, without waiting for USCIS approval, provided your current H-1B has been approved for at least 180 days. The new employer files a fresh LCA and I-129 covering your specific Performance Engineer duties and worksite.
Does remote work create complications for H-1B Performance Engineers?
It can. If you work remotely from a location not listed on your original LCA, your employer may need to post a new LCA notice and update the filing with DOL before you begin work at that location. Full-time remote arrangements across multiple states require careful coordination with HR and your employer's immigration counsel to keep your status compliant.