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Gpu Programming Jobs in Boston, MA (NOW HIRING)

Proven experience in large processors and/or GPU/SOC designs * Handsโ€‘on experience in directed or ... Strong Objectโ€‘Oriented Programming skills * Solid Understanding of Design Verification (DV ...

Senior Software Engineer

Marlborough, MA ยท On-site

$127K - $167K/yr

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

Senior Software Engineer

Marlborough, MA ยท On-site

$127K - $167K/yr

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

BASIC QUALIFICATIONS - PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience - Strong programming skills in modern Python and/or C++ and experience with GPU programming (CUDA ...

CUDA / GPU Programming * Digital Signal Processing * Service oriented architecture or microservice architecture. * Video processing and streaming protocols * AWS development and deployment * Database ...

Senior Machine Learning Engineer

Boston, MA ยท 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 ...

CUDA / GPU Programming * Digital Signal Processing * Service oriented architecture or microservice architecture. * Video processing and streaming protocols * AWS development and deployment * Database ...

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

Showing results 41-60

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 Sep 5, 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 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 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 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:

Infographic showing various Gpu Programming job openings in Boston, MA as of August 2026, with employment types broken down into 1% Internship, 82% Full Time, 12% Part Time, 4% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $70,588 per year, or $33.9 per hour.

HPC/ GPU Cluster Architect

The San Francisco Compute Company

Boston, MA โ€ข On-site

$140 - $200/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Job description

We're building the company which will de-risk the largest infrastructure build-out in history.

When people finance GPU clusters, the datacenters housing them, and the infrastructure powering them, they need "offtake" - meaning someone has signed a contract to lease the cluster for a period of time before its even built.

Financing a GPU cluster is inherently risky, since margins are thin and volumes are huge. Lenders don't want to take on the risk that cluster developers can't repay their loan, and cluster developers really don't want to risk not selling their cluster. As a result, risk is offloaded to the customer using fixed-price long-term contracts.

If you don't mitigate this customer risk, there's a bubble. This isn't SaaS anymore - application layer companies sign multi-year contracts for computer and inference, but sell to customers on monthly subscriptions. If you mess up a purchase, it's game over: a minor shift in your revenue growth rate might mean the difference between profit or bankruptcy. But what if companies could exit their contract by selling it back to the market?

Otherwise, as AI scales, compute only becomes available to folks who can effectively take on that risk. A 2-person startup in a San Francisco Victorian can't realistically sign a 5-year take or pay contract on $100m supercomputers. But they may be able to buy the month of liquidity that someone else sold back.

So that's what we make: a liquid market for GPU offtake.

About the Role

GPU clusters are some of the most performant computers on the planet. Even smaller clusters by todayโ€™s standards would have ranked in the TOP500 five years ago. Our infrastructure team is responsible for architecting and deploying new clusters around the world and keeping them running smoothly. Youโ€™ll participate in on-call rotation, deploy new environments, fix issues when they arise, and lean into automation to enable deployments at scale. Weโ€™re a small but ambitious team so youโ€™ll be an early contributor helping to shape culture, mentor junior engineers, and learn from our customers.

About You
  • You will have 5+ years of experience with handsโ€‘on designing, architecting and scaling at least one HPC or GPU compute cluster in production (ideally >1,000 GPUs, but not required)
  • You deeply understand server hardware fundamentals, including GPUs, NICs, PCIe, memory, thermals, and power
  • Youโ€™re comfortable debugging performance and reliability issues across hardware, OS, drivers, and networking layers; full-stack.
  • The idea of automating fleet operations (provisioning, monitoring, remediation) excites you โ€” you embrace infrastructure-as-code
  • You appreciate, value, and generate strong operational documentation and runbooks
  • You have the ability and willingness to mentor junior engineers and contribute to team culture
  • Youโ€™re open to coming in to our San Francisco office 3โ€“4 days per week
  • Youโ€™re open to domestic travel when required
Some Nice to Haves
  • Familiarity with data center operations including power, cooling, and colo/vendor engagements
  • Strong Linux systems administration experience, including kernel drivers, RDMA stack tuning, and performance analysis
  • Experience with schedulers and orchestration systems such as Slurm and Kubernetes
  • Exposure to virtualization technologies (KVM, QEMU, libvirt)
  • Experience utilizing telemetry pipelines for predictive hardware failure detection
  • Experience troubleshooting high-speed fabrics such as InfiniBand and/or RoCEv2 Ethernet
Benefits Generous equity grant

Team members are offered a competitive salary along with equity in the company

Visa Sponsorships

Yes, we sponsor visas and work permits

Retirement matching

We match 401(k) plans up to 4%

Medical, dental & vision

We offer competitive medical, dental, vision insurance for employees and dependents and cover 100% of premiums

Time off

We offer unlimited paid time off as well as 10+ observed holidays

Parental leave

We offer biological, adoptive, and foster parents paid time off to spend quality time with family

Daily lunch

We cover lunch daily for employees

Unlimited office book budget

You can buy as many books for the office as you want

The San Francisco Compute Company is committed to maintaining a workplace free from discrimination and harassment.

We make employment decisions based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, belief, national origin, social or ethical origin, age, physical, mental, or sensory disability, sexual orientation, gender identity or expression, marital status, civil union or domestic partnership status, past or present military service, HIV status, family medical history or genetic information, family or parental status including pregnancy, or any other status protected by law.

We welcome the opportunity to consider qualified applicants with prior arrest or conviction records. Our commitment to diversity includes hiring talented individuals regardless of their criminal history, in accordance with local, state, and federal laws, including San Franciscoโ€™s Fair Chance Ordinance and Californiaโ€™s ban-the-box laws.

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