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Temporary Software Engineer Gpu Jobs (NOW HIRING)

Software Engineer, GPU Infrastructure

San Francisco, CA · On-site

$203K - $241K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... software. Speed and scale are our key differentiators. Come be a part of building civilization ... The Production Engineering Team Examples of key exciting problems the team is working on * Build ...

Software Engineer, GPU Infrastructure

San Francisco, CA · On-site

$173K - $224K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... software. Speed and scale are our key differentiators. Come be a part of building civilization ... The Production Engineering Team Examples of key exciting problems the team is working on * Build ...

Senior Software Engineer, GPU Performance

Sunnyvale, CA · On-site

$143K - $189K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with compiler optimization, code generation, and runtime systems for GPU architectures (OpenXLA, MLIR, Triton, etc.). About the job Google's software engineers develop the next-generation ...

Software Engineer, GPU Infrastructure (HPC)

$110K - $144K/yr

The Staff Software Engineer will build and operate GPU/TPU superclusters, collaborating closely with AI researchers to enhance infrastructure for AI workloads. Responsibilities : • Build and scale ...

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Temporary Software Engineer Gpu information

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How much do temporary software engineer gpu jobs pay per year?

As of Aug 15, 2026, the average yearly pay for temporary software engineer gpu in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a temporary software engineer GPU, and why are they important?

To thrive as a Temporary Software Engineer GPU, you need a solid background in computer science, experience with GPU programming (such as CUDA or OpenCL), and proficiency in languages like C++ or Python. Familiarity with GPU development environments, debugging tools, and version control systems, along with any relevant certifications, is highly valuable. Strong problem-solving abilities, adaptability, and effective teamwork skills help set candidates apart in this fast-evolving field. These skills enable efficient development, optimization, and integration of GPU-accelerated applications, which is crucial for meeting project deadlines and technical goals.

What does a temporary software engineer GPU do?

A Temporary Software Engineer GPU is responsible for designing, developing, and optimizing software that interacts with graphics processing units (GPUs), typically for a specific project or short-term period. Their duties may include writing code to improve GPU performance, working on graphics or compute-intensive applications, and collaborating with hardware and software teams to ensure efficient GPU utilization. These roles are often contract-based and require strong programming skills in languages such as C++ or CUDA, as well as a solid understanding of GPU architectures.

What are the typical projects a temporary software engineer GPU might work on, and how do they collaborate with permanent team members?

As a Temporary Software Engineer GPU, you can expect to be assigned to specific, time-bound projects such as optimizing graphics performance, supporting new hardware integration, or debugging GPU-related issues. You’ll often work closely with permanent engineers, participating in code reviews, daily stand-ups, and cross-functional meetings to ensure alignment and knowledge transfer. Collaboration is key, as you may need to quickly get up to speed with existing codebases and tools, and contribute solutions that fit seamlessly into larger, ongoing projects. The role offers a fast-paced environment where adaptability and strong communication skills are highly valued.

What cities are hiring for Temporary Software Engineer Gpu jobs?

Cities with the most Temporary Software Engineer Gpu job openings:

What are the most commonly searched types of Software Engineer Gpu jobs?

The most popular types of Software Engineer Gpu jobs are:

What states have the most Temporary Software Engineer Gpu jobs?

States with the most job openings for Temporary Software Engineer Gpu jobs include:

Software Engineer, GPU Infrastructure

Fluidstack

San Francisco, CA • On-site

$203K - $241K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 10 days ago


Job description

About Fluidstack
We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.
We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.
We hire people who care deeply about this problem space. If that is you, please apply!
How We Operate
  • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
  • Velocity. We drive everything forward as fast as possible.
  • First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.
The Production Engineering Team
Examples of key exciting problems the team is working on
  • Build the repair pipeline that keeps pace with a fleet of 10s to 100s of GWs: at our scale, a GPU failure isn't a ticket. It's a throughput problem. We're building the automation that takes a chip from fault detection through triage, RMA, and return to service without human intervention.
  • Qualify every new GPU generation inside a 6-month build window: our platform covers burn-in, performance baselining, and NPI execution. It has to define "production-ready" before a site goes live, not after. New hardware gets certified at speeds unheard of in the industry.
  • Migrate live compute at construction speed: we're converting clusters across production sites simultaneously, bringing new sites online, and making Kubernetes-orchestrated bare metal sustainable at the pace we're building - multiple GW annually.
  • See and own the entire fleet in real time, at any scale: build the observability and orchestration layer that makes hyperscale AI compute actually operable. Debug, tune, and performance-test infrastructure that grows by another site every few months.
Role Scope
  • Own compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU in production - across Kubernetes-orchestrated workloads and bare metal, at scale.
  • Turn deployment/repair into a pipeline, not a procedure. Build and own the automation that takes a compute failure from detection through triage, parts management, and return to service. No one-off scripts, no heroics.
  • Design and expand the GPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU generation. You define what "good" looks like before hardware goes into production.
  • Own Redfish and BMC tooling. Firmware-level telemetry, log collection at fleet scale, and the low-level access layer that repair automation and health tooling depend on.
  • Own end-to-end reliability, scalability, and operation of the compute fleet at-scale. Fluidstack is building one of the largest GPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.
What We're Looking For
The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.
  • You treat toil as a bug. Manual steps in a repair workflow are a backlog item, not a job description.
  • You have an instinct for hardware. You're comfortable reasoning about failure modes at the firmware and silicon level, not just the software stack above it.
  • You move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else.
  • You learn at a steep slope. You reach real competence in an unfamiliar domain fast. We value this over existing expertise.
  • You carry a pager without flinching. You run the incident, write the postmortem, fix the systemic cause, and move on.
  • You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day.
  • You've shipped production automation that other teams depend on, and you're comfortable in any language using AI coding tools.
  • Bonus: Hardware lifecycle management and RMA automation. BMC/Redfish or IPMI tooling. GPU qualification or burn-in frameworks. Workflow and orchestration engines (Temporal, Cadence). Metrics and alerting pipelines (Prometheus, Grafana). Go or Python...

Salary & Benefits
  • Competitive total compensation package (salary + equity).
  • Retirement or pension plan, in line with local norms.
  • Health, dental, and vision insurance.
  • Generous PTO policy, in line with local norms.

Total compensation may also include equity in the form of restricted stock units.
We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.