ZipRecruiter

Log In

1

Gpu Jobs (NOW HIRING)

Baseten

Software Engineer - GPU Kernels

New York, NY · On-site

$180K - $360K/yr

As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced ...

Apple

GPU RTL Design Engineer

San Diego, CA · On-site

As a member of Apple's GPU Design team, you will develop power efficient, high-performance 3D graphics processor micro-architectures targeted for low power mobile devices and high-performance ...

Anthropic

Performance Engineer, GPU

San Francisco, CA · On-site

$280K - $850K/yr

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 ...

Apple

GPU Design Verification Engineer

Santa Clara, CA · On-site

$159.70K - $195K/yr

The GPU Design Verification Engineer will be responsible for the pre-silicon RTL verification of sub-units in the Apple GPU. This includes deep understanding of the micro-architectural details of ...

Xoriant Corporation

GPU Software Engineer

Austin, TX

GPU Software Engineer Location: Austin, TX Duration: Long Term Contract Roles and Responsibilities: * As a GPU Software Engineer, you will be equipped to develop GPU IP from the early Architectural ...

Intel

GPU Logic Design Engineer

Folsom, CA

As a GPU Logic Design Engineer, you will play a vital role in developing cutting-edge graphics IPs required for next-generation GPU designs. By leveraging your expertise in logic design and RTL ...

Nvidia

Senior GPU Memory Architect

Austin, TX

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world-changing solutions for autonomous vehicles, AI, gaming, mobile systems. What you will be doing:

Apple

Graphics (GPU) Architectural Modeling Engineer

Austin, TX · On-site

$138.80K - $171.50K/yr

As a Graphics (GPU) Architectural Modeling Engineer, you will:- Develop architectural models for the development, validation, and verification of graphics processing unit (GPU) design.- Write bit ...

Apple

GPU Silicon Prototype Engineer

Austin, TX · On-site

$35.50 - $39.75/hr

Join Apple's GPU team and contribute to the creation of graphics processing technology that powers millions of devices worldwide. As part of our growing team, you'll work on pre-silicon validation of ...

Microsoft

Senior Researcher - GPU Performance

Redmond, WA · On-site

$158.40K - $258K/yr

We are looking for a Senior Researcher - GPU Performance - Hardware/Software Codesign researcher to explore hardware/kernel-level optimizations to deliver significant efficiency gains for Large ...

Apple

GPU Performance Modeling Engineer

San Diego, CA

$139.50K - $258.10K/yr

Description As a GPU performance modeling engineer, you will be responsible for developing cycle-approximate perf C/C++ models in close collaboration with architects and designers. Additionally, you ...

next page

Showing results 1-20

People also search for

All JobsGpu Jobs

Gpu information

See salary details

$13

$54

$71

How much do gpu jobs pay per hour?

As of May 31, 2026, the average hourly pay for gpu in the United States is $54.94, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $64.90 per hour, depending on experience, location, and employer.

What is a GPU job?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

What are the key skills and qualifications needed to thrive as a GPU Engineer, and why are they important?

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

More about Gpu jobs
What cities are hiring for Gpu jobs? Cities with the most Gpu job openings:
What are the most commonly searched types of Gpu jobs? The most popular types of Gpu jobs are:
What states have the most Gpu jobs? States with the most job openings for Gpu jobs include:
What job categories do people searching Gpu jobs look for? The top searched job categories for Gpu jobs are:
Gpu jobs near you
Infographic showing various Gpu job openings in the United States as of May 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $114,281 per year, or $54.9 per hour.
Software Engineer - GPU Kernels

Software Engineer - GPU Kernels

Baseten

New York, NY • On-site

$180K - $360K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago

Job description

ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.
THE ROLE
We're seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications.
You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work.
EXAMPLE INITIATIVES
You'll get to work on these types of projects as part of our Model Performance team:
  • Baseten Embeddings Inference: The fastest embeddings solution available
  • The Baseten Inference Stack
  • Driving model performance optimization

RESPONSIBILITIES
Core Engineering Responsibilities
  • Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing
  • Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques
  • Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap

Performance & Innovation
  • Implement cutting-edge features like quantization (FP8/FP4), sparsity, and compute/communication overlap
  • Identify and resolve performance bottlenecks using tools like Nsight Systems, Nsight Compute, and Torch Profiler
  • Collaborate with research teams to productionize theoretical advancements

Impact & Collaboration
  • Contribute to internal and open-source GPU libraries
  • Present technical contributions at industry conferences (e.g., NVIDIA GTC, AWS re:Invent)

REQUIREMENTS
  • Strong understanding of GPU architecture and programming paradigms:
    • Memory hierarchy (global, shared, registers, L1/L2 cache)
    • Thread/block/grid organization
    • Synchronization techniques and race condition mitigation
  • Proficient in C++ and GPU performance profiling tools
  • Knowledge of:
    • CUDA C++ API
    • Memory access patterns and bandwidth optimization
    • Numerical precision and quantization strategies
    • Modern GPU features (e.g., tensor cores, async operations)

NICE TO HAVE
  • Experience with Transformer models and attention optimization (e.g., Flash Attention)
  • Familiarity with GPU kernel libraries: Cutlass, Triton, Thrust, CUB
  • Background in GEMM tuning and distributed/multi-GPU compute
  • Contributions to open-source GPU projects
  • Research publications or conference presentations on GPU performance

BENEFITS
  • Competitive compensation, including meaningful equity.
  • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
  • Paid parental leave
  • Fertility and family-building stipend through Carrot
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Apply