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Remote Gpu Programming Jobs in Chicago, IL (NOW HIRING)

Senior HPC Applications Engineer

Chicago, IL · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

A quarter here can include standing up a GPU cluster for one of those communities, federating a ... Jupyter, remote visualization, or virtual desktop support for research users. Benefits Medical ...

Senior HPC Applications Engineer

Chicago, IL · Remote

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

A quarter here can include standing up a GPU cluster for one of those communities, federating a ... Jupyter, remote visualization, or virtual desktop support for research users. Benefits Medical ...

Enterprise Account Executive

Chicago, IL · Remote

$280K - $330K/yr

  • Medical

  • Dental

  • Vision

  • Life

You will be selling a technical platform that solves critical problems for Engineering, DevOps, ... and we have a remote-first work culture. We are the leading platform for operating GPU ...

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and ...

Remote Gpu Programming information

See Chicago, IL salary details

$34K

$66.9K

$98.4K

How much do remote gpu programming jobs pay per year?

As of Aug 15, 2026, the average yearly pay for remote gpu programming in Chicago, IL is $66,933.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $82,400.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals in remote GPU programming roles, and how can they be addressed?

Remote GPU programming roles often involve unique challenges such as managing high-latency connections to remote servers, troubleshooting hardware-specific issues without physical access, and ensuring code compatibility across different GPU architectures. Effective communication with distributed teams is crucial, as is using robust remote debugging tools and version control systems. Staying proactive with documentation and regularly syncing with team members can help address these obstacles and support successful project delivery.

What is remote GPU programming?

Remote GPU programming refers to the practice of developing and running code that utilizes graphics processing units (GPUs) on computers or servers that are accessed over a network, rather than on your local machine. This approach allows developers to leverage powerful, often cloud-based, GPU resources to handle computationally intensive tasks like machine learning, scientific simulations, or rendering without needing specialized hardware themselves. It often involves using remote desktop tools, cloud platforms, or custom APIs to access and manage GPU resources remotely.

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

To thrive as a Remote GPU Programmer, you need in-depth knowledge of parallel computing, proficiency in programming languages like C/C++, and experience with GPU architectures, often backed by a degree in computer science or a related field. Familiarity with technical tools such as CUDA, OpenCL, and GPU profiling/debugging systems is commonly required, along with certifications in GPU programming or high-performance computing. Strong problem-solving abilities, self-motivation, and effective remote communication skills help individuals excel in distributed teams. These competencies are crucial for efficiently developing and optimizing GPU-accelerated applications while collaborating across remote environments.

What are the most commonly searched types of Gpu Programming jobs in Chicago, IL?

The most popular types of Gpu Programming jobs in Chicago, IL are:

What job categories do people searching Remote Gpu Programming jobs in Chicago, IL look for?

The top searched job categories for Remote Gpu Programming jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Remote Gpu Programming jobs?

Cities near Chicago, IL with the most Remote Gpu Programming job openings:

Infographic showing various Remote Gpu Programming job openings in Chicago, IL as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $66,933 per year, or $32.2 per hour.

Senior HPC Applications Engineer

Parallel Works

Chicago, IL • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Job description

About Parallel Works
Parallel Works builds and operates ACTIVATE, a control plane for high performance computing and AI. Our customers run large scientific and AI workloads across their own on-premises clusters, Government and commercial cloud, and commercial GPU providers, and ACTIVATE gives them one way in to all of it. The high security boundary is authorized at Impact Level 5, with FIPS validated cryptography and STIG hardening throughout.
The work reaches most fields that depend on computing at scale: weather and climate forecasting, defense and intelligence programs, aerospace and structural analysis, molecular and materials science, energy, and AI research. A quarter here can include standing up a GPU cluster for one of those communities, federating a laboratory's existing on-premises system with burst capacity it did not have before, and getting a domain code written decades ago to run on current hardware.
Customer success sets our priorities. We are a small engineering company, so engineers here work directly with the people using the systems and carry a problem from the first report through to the fix. This is what we call mission engineering: understanding what a customer is trying to accomplish and why the computing matters to it.
About the role
Parallel Works is hiring a Senior HPC Applications Engineer to own the software stack and the user experience on our platforms. Our users are weather modelers, computational chemists, aerospace engineers, and AI researchers. The role is the escalation point for build failures, jobs that die partway through a multi-node run, and jobs running below expected throughput.
The scope covers both long-lived domain codes and current AI workloads, since customers run both on the same clusters. Users also move between on-premises systems, cloud, and commercial GPU providers, so a large part of the job is making an application behave the same across different compilers, site modules, MPI builds, and filesystems. Expect to spend a good share of the week talking to users.
What you will do
  • Software stack: compile and package MPI implementations (OpenMPI, MPICH, Intel MPI, HPC-X), compilers (GCC, Intel oneAPI, NVHPC), and scientific libraries, delivered through Spack or EasyBuild with Lmod module trees users can navigate.
  • Enable AI and ML workloads: install the frameworks customers ask for, get multi-node GPU launch working, and diagnose what sits below the framework: NCCL and collective behavior, container and driver mismatches, storage throughput, node faults mid-run. Customers drive their own toolchain choices.
  • Performance work: run scaling studies, profile with Nsight, VTune, TAU, HPCToolkit, or Score-P, and hand the finding to the systems team when the fix belongs in the fabric or the filesystem.
  • Portability: get customer codes running on new GPU architectures and new venues, using containers where that beats rebuilding against each site's modules.
  • User support: triage tickets, diagnose failed jobs to a root cause, and close them with a written explanation.
  • Documentation and training: user guides, office hours, and training for user communities, including formal Government training events.

Requirements
  • 10 or more years supporting scientific or AI application users on Linux HPC systems.
  • Building complex software from source on both RHEL family and Debian or Ubuntu systems: compilers, MPI, CMake and autotools, and the dependency problems that come with them.
  • Running Spack or EasyBuild and Lmod in production.
  • Experience with multi-node GPU workloads from the platform side, and the judgment to tell a framework problem from an environment problem.
  • Working with site provided software stacks on on-premises systems as well as cloud images where you control the whole stack.
  • Working knowledge of at least one application domain: weather and climate, computational fluid dynamics, molecular and materials science, or structural analysis.
  • United States citizenship and eligibility for a Secret clearance, since the work reaches export controlled Government environments. An active clearance is helpful but not required. We sponsor candidates who are eligible but not currently cleared.

You do not need every item on this list. If you have most of it and work well with other people, apply.
Preferred Qualifications
  • A prior user facing role at a Government supercomputing center, national laboratory, or university HPC center.
  • Depth in profiling and debugging tools: a GPU profiler, a CPU profiler, gdb, and MPI tooling.
  • Hands-on distributed training or inference work with PyTorch DDP or FSDP, DeepSpeed, Megatron style frameworks, JAX, vLLM, or TensorRT-LLM. Customers own their toolchains, so this is depth rather than a requirement.
  • Jupyter, remote visualization, or virtual desktop support for research users.

Benefits
Medical, vision, and dental coverage, a 401(k) with company match, short term disability, and generous paid vacation and sick time.
Equal employment opportunity
Parallel Works is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic protected by law.