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Gpu Programming Jobs in Boston, MA (NOW HIRING)

Proven experience in large processors and/or GPU/SOC designs * Hands‑on experience in directed or ... Strong Object‑Oriented Programming skills * Solid Understanding of Design Verification (DV ...

New

GPU programming (CUDA/OpenCL) is preferred. * Innovative approach in development of multi-functional medical instruments including image processing / creating software documentation / writing and ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

Experience with camera geometry, 3D reconstruction, or GPU programming (e.g., CUDA, Triton) is a plus. Working Conditions: * Office Only: Works in an office environment in Boston, MA * 3 days in ...

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Gpu Programming information

See Boston, MA salary details

$35.9K

$70.6K

$103.8K

How much do gpu programming jobs pay per year?

As of Aug 14, 2026, the average yearly pay for gpu programming in Boston, MA is $70,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,900.00 and $86,900.00 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 Boston, MA?

The most popular types of Gpu Programming jobs in Boston, MA are:

What are popular job titles related to Gpu Programming jobs in Boston, MA?

For Gpu Programming jobs in Boston, MA, the most frequently searched job titles are:

Infographic showing various Gpu Programming job openings in Boston, MA as of August 2026, with employment types broken down into 4% Internship, 86% Full Time, and 10% Contract. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $70,588 per year, or $33.9 per hour.

Senior Software Engineer - GPU Local AI Platforms

Nvidia

Westford, MA

$127K - $167K/yr

Full-time

Posted 20 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies


Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA's Local AI team is building the software stack that makes large language models and generative AI applications run at maximum efficiency on NVIDIA edge AI hardware. The AI ecosystem moves fast; our job is to make sure end users get the best experience. We own the platform - performance, CI/CD pipelines, validated recipes, and model bring-up infrastructure - that lets developers run groundbreaking LLMs out of the box. The open-source community builds fast; our platform is what turns community innovation into something developers and partners can rely on at scale.

What you'll be doing:

  • Track and evaluate innovations in leading open-source LLM inference frameworks - identify performance-critical features and algorithmic improvements relevant to NVIDIA edge AI hardware

  • Analyze how new model architectures and inference algorithms (attention variants, MoE routing, speculative decoding, multi-token prediction, quantized inference) map onto NVIDIA GPU architecture - identify mismatch, fallback paths, and optimization opportunities

  • Characterize multi-node inference behavior: collective communication primitives (NCCL/RCCL), topology-aware all-reduce strategies, and parallelism efficiency on edge cluster configurations

  • Produce performance analysis reports mapping theoretical hardware limits (memory bandwidth, FLOP/s, interconnect throughput) to observed inference throughput, latency, and utilization

  • Own the model validation workflow for new model releases: architecture compatibility assessment, inference recipe development, performance characterization, and publication to developer recipe sites

  • Develop and maintain developer-facing inference recipes: keep them accurate as frameworks evolve, automate staleness detection, and build feedback loops from CI results to recipe updates

  • Engage with community and partners on model bring-up questions; serve as the technical point of contact for hardware-specific inference issues related to partner concerns

What we need to see:

  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.

  • 12+ years of software engineering with depth in GPU computing, ML systems, or high-performance inference

  • Strong Python or C++ programming, software design, and software engineering skills.

  • Hands-on experience with GPU kernel development or optimization (CUDA/C++, Triton, or equivalent) - you understand how thread blocks, memory hierarchy, and warp execution affect real-world performance

  • Working knowledge of LLM inference internals: attention mechanisms, KV-cache management, continuous batching, quantization formats, and tensor parallelism

  • Container engineering expertise: multi-architecture Docker or OCI builds, layer optimization, runtime configuration, NVIDIA Container Toolkit

  • Strong analytical skills: ability to form a performance hypothesis, design an experiment, interpret results, and communicate findings clearly

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 28, 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.

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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

Year founded

1993