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Cuda Programmer Jobs in New York (NOW HIRING)

Spiral

Software Engineer - Systems

New York, NY · On-site

$200K - $275K/yr

Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such ... PyTorch, CUDA) is also a plus * Experience with Rust is a bonus * Willingness to work in-person at ...

Spiral

Software Engineer - Systems

New York, NY · On-site

$189K - $224K/yr

Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such ... PyTorch, CUDA) is also a plus * Experience with Rust is a bonus * Willingness to work in-person at ...

Fireworks AI

MTS, Research Engineer

New York, NY · On-site

$210K - $320K/yr

Experience with low-level GPU programming (CUDA/Triton) or hardware co-design. * Familiarity with the challenges of training Large Language Models (LLMs) * Familiarity with the challenges of ...

Jobzhr

Software Engineer - Model Products

Manhattan, NY · On-site

$180 - $360/hr

Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten's Model ... Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA ...

Pangram

Machine Learning Engineer (Junior)

New York, NY · On-site

$135K - $150K/yr

Experience with NVIDIA GPU programming and CUDA * Experience with distributed training frameworks, such as DeepSpeed, FSDL, Ray * Experience with inference frameworks like vLLM * Experience with ...

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How much do cuda programmer jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for cuda programmer in New York is $43.25, according to ZipRecruiter salary data. Most workers in this role earn between $28.12 and $56.30 per hour, depending on experience, location, and employer.

What is a cuda programmer?

A CUDA Programmer develops high-performance parallel computing applications using NVIDIA's CUDA (Compute Unified Device Architecture) framework. They optimize algorithms to run efficiently on GPUs, accelerating tasks such as machine learning, scientific simulations, and real-time data processing. This role requires proficiency in C/C++, an understanding of GPU architectures, and experience with parallel computing concepts to maximize performance.

What are the key skills and qualifications needed to thrive as a cuda programmer?

To thrive as a Cuda Programmer, you need strong programming skills in C/C++ and parallel computing, with a solid understanding of GPU architectures and CUDA development. Familiarity with CUDA libraries, performance profiling tools, and platforms like NVIDIA Nsight or Visual Studio is often required, while certifications from NVIDIA can be advantageous. Problem-solving abilities, attention to detail, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can optimize complex algorithms, work efficiently on high-performance computing projects, and collaborate smoothly with multidisciplinary teams.

What are the most common challenges faced by cuda programmers in their daily work?

Cuda Programmers often encounter challenges related to optimizing code performance and efficiently managing memory on GPU architectures. Debugging and profiling can be complex, as issues may arise from both the code and hardware-specific elements, requiring close attention to parallelization and bottlenecks. Collaboration is key, as you’ll typically work closely with software engineers, data scientists, or researchers to integrate and optimize code for specialized workflows. Successfully navigating these challenges helps drive significant performance improvements and innovation in high-performance computing applications.

What are the most commonly searched types of Cuda Programmer jobs in New York?

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For Cuda Programmer jobs in New York, the most frequently searched job titles are:

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Cuda Programmer jobs near you
Infographic showing various Cuda Programmer job openings in New York as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 72% In-person, and 28% Remote job distribution, with an average salary of $89,967 per year, or $43.3 per hour.

Senior AI Performance and Efficiency Engineer

Nvidia

New York, NY • On-site

$114K - $157K/yr

Full-time

Re-posted yesterday

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

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!

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.

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

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.

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

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