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Gpu Programming Jobs in New York (NOW HIRING)

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Machine Learning Engineer

New York, NY · On-site

NVIDIA GPU programming (Triton, CUTLASS, custom CUDA kernels) and deep NCCL knowledge * FP8 or FP4 training experience * Familiarity with TorchTitan, SGLang, vLLM, Megatron, etc. * Track record of ...

Fireworks AI

MTS, Research Engineer

New York, NY · On-site

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 ...

Baseten

Software Engineer - GPU Kernels

Manhattan, NY · On-site

Required : • Strong understanding of GPU architecture and programming paradigms: Memory hierarchy (global, shared, registers, L1/L2 cache), Thread/block/grid organization, Synchronization ...

Baseten

Software Engineer - GPU Kernels

New York, NY · On-site

$180K - $360K/yr

Invent) REQUIREMENTS * Strong understanding of GPU architecture and programming paradigms: * Memory hierarchy (global, shared, registers, L1/L2 cache) * Thread/block/grid organization

Rutgers University

Research Programmer

Piscataway, NJ · On-site

$120K - $130K/yr

Experience with GPU programming and optimization for ML models, utilizing frameworks, like CUDA or OpenCL • Experience with applied computer vision, such as convolutional neural networks and vision ...

Modal, Inc

Forward Deployed Engineer - ML

New York, NY · On-site

$180K - $250K/yr

... GPU programming, or ML infrastructure * Familiarity with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains. You don't need all of these, but you should be able to go ...

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Gpu Programming information

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$36.1K

$71.1K

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How much do gpu programming jobs pay per year?

As of Aug 7, 2026, the average yearly pay for gpu programming in New York is $71,084.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,200.00 and $87,500.00 per year, depending on experience, location, and employer.

What is GPU programming?

A GPU Programming job involves writing and optimizing code to run on Graphics Processing Units (GPUs) for parallel computing tasks. This role is commonly found in fields like machine learning, scientific computing, gaming, and data analytics. GPU programmers use languages such as CUDA, OpenCL, or Vulkan to accelerate computations and improve performance. They work closely with software engineers and data scientists to optimize algorithms for high-performance applications.

What are the key skills and qualifications needed to thrive in GPU programming, and why are they important?

To excel in GPU Programming, you need a strong background in parallel computing concepts, mathematics, and proficiency in languages such as CUDA, OpenCL, or DirectX/OpenGL, often supported by a degree in computer science, engineering, or a related field. Familiarity with NVIDIA and AMD GPU development tools, performance profilers, and possibly certifications like NVIDIA's Deep Learning Institute courses are valuable. Teamwork, effective communication, and strong problem-solving abilities are essential soft skills in this field. These competencies enable efficient development, optimization, and integration of high-performance GPU code in real-world applications.

What types of projects or applications do GPU programmers commonly work on?

GPU Programmers are often involved in developing or optimizing software for high-performance applications such as machine learning, scientific simulations, real-time rendering in gaming and visualization, and video/image processing tools. Their daily work may include collaborating with software engineers, data scientists, and hardware teams to create efficient, scalable parallel algorithms that leverage GPU capabilities. The role frequently requires problem-solving to maximize computational efficiency and troubleshooting complex performance bottlenecks. By working across multidisciplinary teams, GPU Programmers help deliver robust solutions for data-intensive problems in areas like healthcare, finance, automotive technology, and entertainment.

What are the most commonly searched types of Gpu Programming jobs in New York? The most popular types of Gpu Programming jobs in New York are:
What are popular job titles related to Gpu Programming jobs in New York? For Gpu Programming jobs in New York, the most frequently searched job titles are:
What job categories do people searching Gpu Programming jobs in New York look for? The top searched job categories for Gpu Programming jobs in New York are:
Gpu Programming jobs near you
Infographic showing various Gpu Programming job openings in New York as of August 2026, with employment types broken down into 1% Internship, 79% Full Time, 14% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $71,084 per year, or $34.2 per hour.

GPU Performance Engineer

Two Sigma Investments, LP

New York, NY • On-site

$165K - $300K/yr

Full-time

Medical, Dental, Life, Retirement, PTO

Re-posted 21 hours ago

Job description

GPU Performance Engineer
Location
NY New York
United States
Business
Investment Management
Function
Engineering
Experience Level
Experienced
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Position Summary
Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.
Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world's most complex economic problems.
Two Sigma is building a new team to drive the firm's strategic transition from CPU-centric to GPU-accelerated computation. Accelerated Compute sits within AI Innovation and operates at the intersection of quantitative modeling workflows, GPU performance engineering, and infrastructure strategy.
You are a GPU programming expert. You write CUDA, you optimize kernels, you understand the memory hierarchy, you know why naive GPU code is slow and how to make it fast. You will ensure that when workloads move to GPU, they achieve the performance that justifies the transition.
You will take on the following responsibilities:
  • Design and implement GPU-accelerated kernels for financial computation workloads
  • Optimize GPU code for throughput, latency, and memory efficiency across current and next-generation hardware (Blackwell, Rubin)
  • Develop procedures for precision management (FP8/FP4 training and inference) in financial applications
  • Profile and optimize GPU workloads using NVIDIA tooling (Nsight Systems, Nsight Compute)
  • Build reusable GPU libraries and abstractions that modeling teams can use without requiring deep CUDA expertise
  • Evaluate and integrate GPU-accelerated libraries (RAPIDS, CUTLASS, cuBLAS, TensorRT) for financial use cases

You should possess the following qualifications:
  • BS or MS in Science, Technology, Engineering or Math
  • Minimum 1 year of experience required; 4-10 years of experience preferred
  • Expert-level CUDA programming: kernel development, memory management, stream and graph optimization
  • Deep understanding of GPU architecture: SM structure, warp scheduling, memory hierarchy (registers, shared memory, L1/L2, HBM)
  • Experience with performance profiling and optimization of GPU workloads
  • Strong C++ and Python skills, as well as familiarity with mixed-precision computation and numerical stability
  • Track record of delivering meaningful speedups on real workloads (not just benchmarks)

Preferred experience:
  • Background in HPC, scientific computing, or computational finance
  • Experience with multi-GPU and multi-node GPU programming (NCCL, MPI)
  • Familiarity with GPU-accelerated data processing frameworks (RAPIDS, cuDF)

You will enjoy the following benefits:
  • Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
  • Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
  • Learning: Tuition reimbursement, conference and training sponsorship
  • Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
  • Hybrid Work Policy: Flexible in-office days with budget for home office setup

The base pay for this role will be between $165,000 and $300,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.
Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
If you believe you need an accommodation, please visit our website for additional information.

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