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Temporary Gpu Programming Jobs (NOW HIRING)

Founding BDR, AI Inference (SF)

San Francisco, CA · On-site

$140K - $150K/yr (+ commission)

... engineering buyers -- tokens/second and latency -- and on cost, backed by GPU procurement ... No closing responsibility yet -- the CEO still closes every deal -- but that's temporary by design ...

This engineer will work closely with cross-functional teams responsible for server, storage, GPU ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

WI · On-site

$131K/yr

Document design and verification intent clearly enough that the next engineer -- or the next ... At least 5 years of hands‑on RTL design experience in SystemVerilog/Verilog for CPU, GPU, or ...

... GPU/NIC experience is a plus • Basic Network experience • Experience reading Linux logs • ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

Systems Administrator

New York, NY · On-site

$80K - $90K/yr

End Date if Temporary: * Hours Per Week: 35 * Standard Work Schedule: * Building: Morningside ... GPU cluster. The successful applicant will learn all aspects of running a research data center ...

Additional Requirements: 1. Programming & data: Python (numpy/pandas), basic R (Seurat/tidyverse ... First Shift (United States of America) Temporary or Regular? This is a regular position FTE ...

Exposure to AI, HPC, GPU, cloud, or accelerated computing environments. * Experience with ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

Exposure to AI, HPC, GPU, cloud, or accelerated computing environments. * Experience with ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

Hardware Engineer

San Francisco, CA · On-site

$145K - $192K/yr

High performance/power edge compute including multi‑CPU platforms with significant GPU resources ... wide temp ranges, IP, and solar loading * High speed signaling including GSML, multi gigabit ...

$54K - $73K/yr

Understanding of CPU, GPU, & FPGA Radar signal processing and control * Understanding of Electrro ... Temporary employees generally are not eligible for BAE Systems benefits, but can elect to ...

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Temporary Gpu Programming information

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How much do temporary gpu programming jobs pay per year?

As of Sep 11, 2026, the average yearly pay for temporary gpu programming in the United States is $64,974.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What is a temporary GPU programmer?

A Temporary GPU Programmer is a professional hired on a short-term basis to develop, optimize, or maintain software that runs on Graphics Processing Units (GPUs). These programmers typically work with languages like CUDA, OpenCL, or DirectX to accelerate complex computations or graphics rendering. Temporary roles may be project-based, such as optimizing machine learning models, scientific simulations, or enhancing graphics in games and applications. Companies often hire temporary GPU programmers to meet specific deadlines, handle workload spikes, or bring in specialized expertise for certain tasks.

What types of projects or tasks are commonly assigned to temporary GPU programming roles?

Temporary GPU programming roles typically focus on short-term, high-impact projects such as optimizing existing code for parallel processing, accelerating specific algorithms, or supporting research and development teams with prototype implementations. You may be tasked with profiling and enhancing the performance of applications using frameworks like CUDA or OpenCL, or assisting with machine learning model training and inference on GPU hardware. Collaboration with data scientists, software engineers, and domain experts is common, and your contributions often involve delivering tangible speedups or enabling new computational capabilities within tight timelines.

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

To thrive as a Temporary GPU Programmer, you generally need strong proficiency in parallel programming, C/C++, and deep knowledge of GPU architectures, often supported by a degree in computer science or a related field. Familiarity with technical tools like CUDA, OpenCL, and GPU profiling/debugging systems is typically required. Problem-solving ability, attention to detail, and effective communication are standout soft skills for this role. These skills ensure efficient development, optimization, and troubleshooting of GPU-accelerated applications in a fast-paced, project-based environment.

What cities are hiring for Temporary Gpu Programming jobs?

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What are the most commonly searched types of Gpu Programming jobs?

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Founding BDR, AI Inference (SF)

San Francisco, CA • On-site

Lavendo
Recruiting and Staffing Services • 1 - 10 employees

$140K - $150K/yr (+ commission)

Full-time

Medical, Dental, Vision, PTO

Posted 15 days ago


Key responsibilities

  • Own 100% of outbound prospecting by targeting CTOs and engineering leads at AI-native companies to generate qualified meetings.

  • Run and optimize 80+ daily touches across email, LinkedIn, and cold calls, building and rewriting outbound sequences based on response rates.

  • Build and establish outbound systems and processes from scratch, preparing for initial meetings with support from the Head of GTM and CEO.


Job description

Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.

About the Company

Our client is building the autonomous performance engineer the AI industry doesn't have enough of: AI agents that optimize GPU kernels so companies can run inference on open-source LLMs faster and cheaper than anyone else. Their product wins on the two numbers that matter most to engineering buyers — tokens/second and latency — and on cost, backed by GPU procurement relationships most seed-stage companies don't have access to.

They're a YC company from a recent batch, having just closed a $4M seed round led by a respected early-stage fund. The angel list is the kind you don't usually see this early: senior technical leaders from Google, OpenAI, Dropbox, and Together AI have personally put money in. If you've spent any time around inference or GPU infra, that's not a vanity signal — it's some of the most technically demanding people in the space betting on this team's approach.

Under 10 people today, real customers running production inference, and a founder who still closes every deal himself. This is about as early as 'early-stage' gets.

The Mission

Make it possible for any team — not just the ones with in-house GPU experts — to serve state-of-the-art open-source models in production at a fraction of the usual latency and cost. Less time hand-tuning kernels, more time shipping product.

The Opportunity

This is a Founding BDR seat — one of the company's first two GTM hires, reporting straight to the Head of GTM & Growth. You'll own 100% of outbound from day one. No closing responsibility yet — the CEO still closes every deal — but that's temporary by design: people who perform get moved to full-cycle AE in weeks to months, not years. The company would rather promote you than hire over you.

There's no outbound playbook here. You're writing it.

Location: On-site 5 days/week in San Francisco
Visa sponsorship: Open to visa transfers (OPT, H-1B transfers, etc.)

What You'll Do
  • Own 100% of outbound prospecting — target: 8+ qualified meetings per week

  • Run 80+ daily touches across email, LinkedIn, and cold calls

  • Book first meetings with the people who actually feel this pain: CTOs and engineering leads at AI-native companies running production inference

  • Build and continuously rewrite outbound sequences, treating your weekly reply and meeting rates as live experiments, not a report you file and forget

  • Build the outbound engine and systems from scratch, not inherit someone else's

  • Walk into every first meeting prepped by the Head of GTM and CEO, never cold

What You Bring
  • Time at an early-stage startup, pre-seed through Series C

  • 1–3 years of full-time, 100% outbound B2B sales development experience

  • Real experience selling technical products to technical buyers

  • Willingness to be in the office in San Francisco 5 days a week

Nice to have:

  • Experience at an inference, GPU infra or voice AI company

  • A technical background (software engineering, or exposure to a technical dev-tools product) — helpful, but not required. A fast learner without an engineering degree is completely fine here

  • Founding SDR or founding GTM experience at a company under 20 people

  • Non-traditional paths welcome: solutions engineers or implementation folks from small startups who've done customer-facing work, or early-career AEs who want to prove themselves on outbound first

Key Success Drivers
  • You want to build, not just execute. The interview process is specifically designed to screen for this — if you're looking for a ready-made playbook, this isn't your seat.

  • You default to high ownership and agency. This is a small team with an accelerator's DNA: move fast, take initiative, don't wait to be told.

  • You're comfortable without a net. There's no established process yet. That should sound exciting, not stressful.

  • You're genuinely curious about the technical problem. You don't need a CS degree, but you need to want to understand this space well enough that a skeptical engineering buyer takes you seriously in the first five minutes.

Why Join?
  • A YC company already beating larger, better-funded competitors on tokens/second and latency

  • An investor and angel list — including senior technical leaders from Google, OpenAI, Dropbox, and Together AI — that gives you a real answer when a prospect (or your own network) asks "why should I trust this team"

  • A genuinely fast path to full-cycle AE — within weeks to months, not years

  • Direct access to the Head of GTM and CEO — no layers, no waiting for feedback

  • $85K–$100K base, ~$140K OTE with uncapped commission — paid monthly against a weekly qualified-meetings target, not tied to lead value or deal size

  • Competitive, early-stage equity

  • 100% covered medical, dental, and vision for you and your dependents

  • Unlimited PTO and parental leave

  • Daily lunch and dinner, plus a $1,000/month housing stipend if you live within 0.5 miles of the office (Dogpatch)

Interviewing Process
  • Intro call with the Head of GTM

  • Interview with the CEO

  • Onsite (half day)

  • Offer

We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.

Compensation Range: $140K - $150K


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About Lavendo

Sourced by ZipRecruiter

Industry

Recruiting and staffing services

Company size

1 - 10 Employees

Headquarters location

San Francisco, CA, US

Year founded

2021