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Ai Compiler Jobs (NOW HIRING)

AI Compiler Engineer

$195K - $265K/yr

About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML ...

AI Compiler Engineer

$195K - $265K/yr

About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML ...

About the Role We're looking for a Front End Compiler Engineer to own the ingestion layer of our high-performance, portable AI compiler. This is where the journey begins - you'll build the systems ...

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Senior AI Compiler Engineer, MLIR

Santa Clara, CA · On-site

$143K - $189K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

You'll help shape the future of AI computing through compiler technology that is fast, flexible, and built for real-world models. This role is hybrid based in Austin, TX. We welcome candidates at ...

Senior AI Compiler Engineer, MLIR

OR · On-site +1

$122K - $161K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

Senior AI Compiler Engineer, MLIR

Santa Clara, CA · On-site

$143K - $189K/yr

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR ...

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Ai Compiler information

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$10

$33

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How much do ai compiler jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for ai compiler in the United States is $33.92, according to ZipRecruiter salary data. Most workers in this role earn between $27.40 and $38.22 per hour, depending on experience, location, and employer.

What is an AI compiler?

AI Compilers are specialized software tools designed to optimize and convert machine learning models or AI code into efficient formats for deployment on various hardware platforms. They help bridge the gap between AI frameworks (like TensorFlow or PyTorch) and hardware accelerators (such as GPUs, TPUs, or custom chips). By automating tasks such as graph optimization, quantization, and parallelization, AI Compilers improve the performance and efficiency of AI models in production environments. Their use is critical for deploying AI applications at scale, especially in resource-constrained or latency-sensitive scenarios.

What are the key skills and qualifications needed to thrive as an AI compiler?

To thrive as an AI Compiler, you need a strong background in computer science, compiler theory, and machine learning, often backed by a relevant degree and experience with programming languages such as C++, Python, or LLVM. Familiarity with AI frameworks (like TensorFlow or PyTorch), optimization tools, and hardware accelerators is typically required, along with knowledge of specialized compilers for AI workloads. Strong problem-solving abilities, attention to detail, and effective communication are the soft skills that set top performers apart in this field. These skills are crucial because they enable efficient development and deployment of AI models on various hardware, ensuring optimal performance and innovation.

What are some typical challenges AI compiler engineers face when optimizing machine learning models for different hardware architectures?

AI Compiler engineers often encounter the challenge of ensuring that machine learning models run efficiently across various hardware platforms, such as GPUs, TPUs, and specialized AI accelerators. This requires a deep understanding of both the model's computational requirements and the hardware's unique capabilities and constraints. Balancing performance, memory usage, and portability while maintaining correctness can be complex, especially as models and hardware evolve rapidly. Collaboration with hardware engineers and ML researchers is common, as is ongoing learning to stay current with new compiler techniques and frameworks.

What is the difference between Ai Compiler vs Data Scientist?

AspectAi CompilerData Scientist
Required CredentialsComputer Science degree, programming skills, knowledge of AI frameworksStatistics, mathematics, programming, often a degree in data science or related fields
Work EnvironmentSoftware development teams, AI research labs, tech companiesData analysis teams, research environments, consulting firms
Industry UsageAI development, machine learning deployment, software engineeringData analysis, predictive modeling, business insights

While both roles involve technical expertise, an Ai Compiler focuses on developing tools that optimize AI model deployment, whereas a Data Scientist analyzes data to generate insights. They often collaborate but serve different functions within AI and data-driven projects.

What cities are hiring for Ai Compiler jobs?

Cities with the most Ai Compiler job openings:

What are popular job titles related to Ai Compiler jobs?

For Ai Compiler jobs, the most frequently searched job titles are:

Infographic showing various Ai Compiler job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $70,561 per year, or $33.9 per hour.

Engineering Manager, AI Compiler Analysis

Santa Clara, CA • On-site

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Re-posted 10 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA's invention of the GPU transformed computer graphics, parallel computing, and modern AI. Today, NVIDIA high-performance processing platforms power breakthroughs across generative AI, autonomous systems, scientific computing, robotics, and high-performance data centers. NVIDIA's compiler technologies are key enablers of AI at scale, turning rapidly evolving deep learning models into highly optimized GPU programs for training and inference.

As AI models, GPU architectures, and compiler systems become more sophisticated, AI compiler quality has become a deep technical challenge at the intersection of compilers, machine learning frameworks, numerical computing, formal reasoning, and large-scale systems engineering. To address these complex challenges, we are seeking an Engineering Manager to spearhead our strategy for verifying AI compilers built for next-generation deep learning workloads. This is a hands-on compiler engineering leadership role for someone who understands where compiler quality can regress in modern AI compiler stacks.

What You'll Be Doing: Lead, mentor, and grow a highly technical team responsible for AI compiler verification. Own the verification of next-generation AI workloads, including LLMs and agentic AI systems, across the full spectrum of the AI compiler stack and execution pipeline. Define formal-verification requirements for AI compiler transformations and generated GPU programs, including formal specifications, tensor/operator semantics, semantic preservation, code equivalence, numerical behavior, and properties stressed by AI-generated or adversarial workloads.

Drive the use of AI-assisted and compiler-aware verification techniques, including adversarial workload generation, differential testing, symbolic reasoning, formal methods, fuzzing, static analysis, and automated debugging. Partner closely with AI compiler development, CUDA software, ML framework, runtime, product, and AI software teams to build scalable verification infrastructure, improve engineering velocity, and increase production confidence. What We Need To See: BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience.

10+ overall years of total relevant software engineering experience, including at least 3 years experience leading engineering teams or major technical initiatives. Experience with AI compiler or framework technologies such as MLIR, TensorRT, XLA, Triton, PyTorch, or JAX. Fluency with AI workload and ML framework concepts, including computation graphs, tensor operations, model execution, and training or inference workflows.

Strong people management skills, including hiring, mentoring, performance management, and team development. Ways To Stand Out From The Crowd: Hands-on with deep learning compiler internals, including compiler IRs, optimization and lowering pipelines, code generation, runtime integration, or production compiler infrastructure. Experience verifying performance-sensitive compiler behavior and root-causing subtle regressions in production AI/ML systems using computational methods, fuzzing, code inspection, or automated debugging.

Background in formal verification or programming languages, with familiarity in formal specifications, theorem proving, Lean, SMT/SAT solvers, or symbolic reasoning. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 2, and 200,000 USD - 322,000 USD for Level 3. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 3, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US