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From Home Gpu Jobs (NOW HIRING)

Lambda

Senior Solution Engineer

San Francisco, CA · On-site

$226K - $355K/yr

One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This ... Lambda's designated work from home day is currently Tuesday. The Lambda Cloud GTM team powers our ...

Lambda

Software Engineer - Compute

San Francisco, CA · On-site

$266K - $395K/yr

One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This ... Lambda's designated work from home day is currently Tuesday. The Compute Software Engineering role ...

Lambda

Head of Sales, Lambda Cloud

San Francisco, CA · On-site

$250 - $350/hr

One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This ... Lambda's designated work from home day is currently Tuesday. Overview Lambda is building the cloud ...

Lambda

Head of Sales, Lambda Cloud

San Francisco, CA · On-site +1

$235K - $315K/yr

One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This ... Lambda's designated work from home day is currently Tuesday. Overview Lambda is building the cloud ...

Socket.dev

VP, Product Marketing

San Francisco, CA · On-site

$250 - $360/hr

One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This ... Lambda's designated work from home day is currently Tuesday. What You'll Do As the VP of Product ...

Wayve

Principal Engineer, Data & Compute

Sunnyvale, CA · Hybrid

$370K - $418K/yr

Cross-Region GPU Job Execution - Build the foundations that enable large-scale AI workloads to run ... ng from home. This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably ...

LinkedIn

Staff Engineer, Hardware Reliability

Sunnyvale, CA · Hybrid

$144K - $191K/yr

The work location of this role is hybrid, meaning it will be performed both from home and from a ... Contribute to AI/ML infrastructure performance and reliability of GPU platforms, InfiniBand/RDMA as ...

LinkedIn

Staff Engineer, Hardware Reliability

Sunnyvale, CA · On-site

$144K - $191K/yr

The work location of this role is hybrid, meaning it will be performed both from home and from a ... Contribute to AI/ML infrastructure performance and reliability of GPU platforms, InfiniBand/RDMA as ...

Bolt Graphics

Lead SoC Architect

Sunnyvale, CA · On-site

$200K - $250K/yr

Evaluate and integrate third-party IPs including CPU, GPU, NPU, PCIe, DDR/LPDDR, Ethernet ... Equity - Stock Options * 401(k) match * WFH Hardware Bolt is committed to building a diverse and ...

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How much do from home gpu jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for from home gpu in the United States is $25.61, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $29.33 per hour, depending on experience, location, and employer.

What is the difference between From Home Gpu vs From Home Data Analyst?

AspectFrom Home GpuFrom Home Data Analyst
Required CredentialsKnowledge of GPU hardware, basic troubleshooting skillsDegree in statistics, data analysis, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote technical support or hardware setupRemote data interpretation and reporting
Industry UsageTechnology, gaming, hardware manufacturingFinance, marketing, healthcare, and tech sectors

From Home Gpu roles focus on hardware knowledge and technical support, often in tech-related industries. From Home Data Analyst positions emphasize data interpretation, analysis skills, and reporting, spanning various sectors. Both roles are remote but require different skill sets and industry focus.

What is a from home GPU job?

'From Home GPU' jobs refer to remote work positions that require access to a powerful Graphics Processing Unit (GPU). These jobs typically involve tasks such as video rendering, machine learning, 3D modeling, or scientific computing, which need significant computational power provided by a GPU. Working from home in these roles allows professionals to use their own GPU-equipped hardware or connect to cloud-based GPU resources to complete their work. Common job titles include remote AI engineer, 3D artist, or video editor. The demand for such jobs has grown as more companies embrace remote work and cloud computing technologies.

What are common challenges faced by remote GPU computing professionals, and how can they be addressed?

Remote GPU computing professionals often encounter challenges such as ensuring reliable access to high-performance hardware, managing data security, and troubleshooting technical issues without on-site support. To address these, it's important to work with reputable cloud GPU providers, maintain secure data transfer protocols, and develop strong remote collaboration skills. Regular communication with IT support and staying updated on remote GPU tools can also help mitigate these challenges, ensuring smooth workflow and project delivery.

What are the key skills and qualifications needed to thrive as a GPU programmer working from home?

To succeed as a remote GPU Programmer, you need strong proficiency in parallel computing, programming languages like C++ and Python, and a solid understanding of computer graphics or machine learning algorithms, often backed by a relevant degree or certifications. Familiarity with tools and frameworks such as CUDA, OpenCL, TensorFlow, and remote collaboration platforms is typically required. Excellent problem-solving abilities, self-motivation, and effective communication skills are crucial for thriving in a remote environment. These skills enable high-quality, efficient development and seamless teamwork, ensuring project success even when working from a distance.
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What cities are hiring for From Home Gpu jobs? Cities with the most From Home Gpu job openings:
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From Home Gpu jobs near you
Infographic showing various From Home Gpu job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $53,274 per year, or $25.6 per hour.

GPU- Physical Design Engineer at Qualcomm San Diego, CA

Itlearn360

San Diego, CA • On-site

$195.20 - $292.80/hr

Other

Posted 6 days ago

Job description

General Summary

Physical implementation of industry leading integrated graphics core designs from netlist to GDS of very complex and high frequency blocks or top level. This includes floor‑planning, placement, clock implementation and routing of very high gate count design to meet very aggressive Power, Performance and Area (PPA) targets. Involves working on latest technology process nodes and employing latest design techniques to push PPA envelope which includes working with RTL design teams to optimize design. Incumbent is also expected to be involved in collaboration with multi‑disciplined teams and tool vendors to develop/enhance automation in flows and methodologies for design efficiency improvement. This role requires understanding of trade‑offs to be made for PPA, hence decisions taken to get the optimal design.

Key Skills & Experience
  • Experience in Physical design which includes floor‑planning, placement, clock implementation, routing for complex, high frequency designs
  • Experience with physical synthesis and implementation tools – Synopsys Fusion Compiler, ICC2 and Cadence Genus/Innovus
  • Must have good knowledge of static timing analysis, reliability and power analysis
  • Strong understanding of CMOS circuit design and design techniques to push Power, Performance and Area of complex designs
  • Ability to think outside the box for innovative solutions to improve power and eliminate performance bottlenecks
  • Strong understanding of GPU micro‑architecture and collaborate with RTL designers to improve bottlenecks for power and performance
  • Solid working knowledge of scripting skills including Tcl, Perl or Python
  • Excellent communication skills and collaboration in a team environment is a must
Preferred Skills
  • Clock, power delivery network design, process technology, prior experience in flow and methodology development, block closure
  • Hands‑on experience with Synthesis, DFT, Place and Route, Timing and Reliability Signoff
  • Hands‑on experience working with very complex designs that push the envelope of Power, Performance and Area
  • Hands‑on experience working with sub‑micron technology process nodes e.g., 5nm, 4nm and below is highly advantageous
  • Prior experience in flow and methodology development is an advantage
  • RTL expertise (Verilog/System Verilog)
  • Excellent debug and analytical skills
  • Ability to work well in a collaborative environment with multi‑disciplined teams
Minimum Qualifications
  • Bachelor’s degree in Electrical/Computer Engineering
  • 10+ years of direct physical design work experience
  • Strong background in VLSI design, scripting
  • Strong background and experience working with industry standard Synthesis and Place and Route tools including Signoff tools
  • Hands‑on experience taping out designs in sub‑micron technology node design < 10nm
  • Expect strong self‑motivation and time management skills
Preferred Qualifications
  • Master’s degree in Electrical/Computer Engineering
  • 8+ years of direct physical design work experience
  • In‑depth end‑to‑end experience from RTL2GDS, taping out at least 6 complex designs in deep sub‑micron technology node
Pay & Benefits

Pay range: $195,200.00 – $292,800.00. Competitive annual discretionary bonus program and opportunity for annual RSU grants. Highly competitive benefits package designed to support your success at work, at home, and at play.

Accessibility & EEO

If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disability‑accomodations@qualcomm.com or call Qualcomm’s toll‑free number. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to participate in the hiring process.

Qualcomm is an equal‑opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected classification.

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