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Intern Software Engineer Gpu Jobs (NOW HIRING)

Futran Tech Solutions Pvt. Ltd.

GPU Software Engineer

$138.20K - $185.30K/yr

GPU Software Engineer Location: USA(Remote) Role Summary We are seeking expert-level GPU Software Engineers to support a high-visibility platform initiative within the Maya program, focused on ...

Nvidia

System Software Engineer - GPU

Santa Clara, CA

$203.20K - $240.80K/yr

We are seeking a System Software Engineer to work on next-generation computing and graphics products. Our charter is to build the most stressful set of applications a GPU or high performance ...

Baseten

Software Engineer - GPU Kernels

$143.30K/yr

Baseten is an innovative company powering AI solutions for leading firms like Notion and OpenEvidence, and they are seeking a GPU Kernel Engineer to enhance AI model performance. This role focuses on ...

Accelerate Learning Inc.

Intern, Software Engineer

POSITION SUMMARY As a Software Engineering Intern, you'll support the design, development, and maintenance of Software Applications and internal tools while working alongside experienced engineers in ...

Google

Senior Software Engineer, GPU Performance

Sunnyvale, CA · On-site

$143.80K - $189.50K/yr

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 ...

Bedgear

Software Engineer Intern

Rock Hill, SC

$25 - $30/hr

Software Engineer Intern ID: 100401 Department: Development Location: Rock Hill, SC Description Job Title : Software Engineer Intern Department : Research & Innovation Reports to: Chief Science ...

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How much do intern software engineer gpu jobs pay per hour?

As of May 29, 2026, the average hourly pay for intern software engineer gpu in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

What is the difference between Intern Software Engineer Gpu vs Intern Software Engineer Cloud?

AspectIntern Software Engineer GpuIntern Software Engineer Cloud
Required CredentialsComputer Science degree or related, programming skills, familiarity with GPU programmingSimilar credentials, with emphasis on cloud platforms and networking
Work EnvironmentHardware-focused, GPU development labs, research teamsCloud infrastructure, remote teams, data centers
Employer & Industry UsageTech companies, hardware manufacturers, AI researchCloud service providers, SaaS companies, enterprise IT

Intern Software Engineer Gpu roles focus on GPU hardware and software development, often involving parallel computing and AI workloads. Intern Software Engineer Cloud positions emphasize cloud infrastructure, deployment, and scalability. Both roles require strong programming skills and industry knowledge but differ mainly in their technical focus and work environment.

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Intern Software Engineer Gpu jobs near you

GPU Software Engineer

Futran Tech Solutions Pvt. Ltd.

Remote

$138.20K - $185.30K/yr

Full-time

Posted 15 days ago

Job description

Job Title : GPU Software Engineer
Location: USA(Remote)
Role Summary
We are seeking expert-level GPU Software Engineers to support a high-visibility platform initiative within the Maya program, focused on building software tooling on top of a custom compiler and SDK.
The role involves developing, optimizing, and porting GPU kernels and AI workloads to a specialized hardware platform.
This is a critical and time-sensitive engagement with immediate onboarding expectations and long-term roadmap alignment (~18 months).
Key Responsibilities
• Develop GPU kernels for specialized hardware platforms using PyTorch/Triton frameworks
• Build software solutions leveraging custom compiler and SDK capabilities
• Design and implement kernel-level optimizations to control hardware execution behavior
• Port open-source AI/ML models to custom SDK environments
• Port and adapt high-performance computing benchmarks and stress workloads such as:
  • Linpack (High Performance Linpack)
  • BERT/benchmark-style workloads (referred as "Babu bench")
    • Develop stress testing and validation workloads aligned to hardware behaviour and platform validation
    • Support testing and stress testing of current and next-generation hardware platforms
    • Collaborate closely with platform architects and compiler teams to enhance system capabilities

Core Technical Skills (Must-Have)
Programming & Frameworks
• Python
• C/C++ (systems-level programming)
• PyTorch
• Triton (Triton language / kernel development)
GPU & Systems Expertise
• GPU kernel development (mandatory and critical)
• Strong understanding of GPU architecture and compute optimization
• Experience with compiler-based optimizations / runtime execution layers
• Experience with custom SDKs or hardware abstraction layers
Performance & Workloads
• Experience in:
  • GEMM kernel development (matrix multiplication kernels)
  • Porting ML models to new hardware platforms
  • Performance tuning and stress testing at system level

Nice-to-Have Skills
• Experience working with custom silicon / hardware platforms
• Exposure to high-performance computing (HPC) workloads
• Familiarity with:
  • Linpack benchmarks
  • AI workload benchmarking tools
    • Experience in compiler optimization ecosystems

Engagement Model & Structure
• Number of roles: 3 developers (initial hiring may start with 2)
• Location flexibility:
  • Onsite / Offshore / Hybrid mix allowed
    • Timeline:
  • Immediate start required
    • Duration:
  • ~18 months program duration with phased platform evolution

Interview Process
• Candidates will undergo direct technical evaluation by program lead
• Strong preference for candidates who can showcase real implementations / past work (hands-on kernel development)
Key Differentiators (Critical Expectation)
• This is NOT a DevOps / support / debugging role
• Requires deep hands-on engineering expertise in:
  • Kernel programming
  • GPU workloads
  • ML framework internals
    • Candidates must demonstrate build-level competence, not just theoretical knowledge

Success Criteria
• Ability to deliver:
  • High-performance kernels
  • Production-ready software for hardware platforms
    • Successful porting of models and workloads to custom environments
    • Contribution to next-generation platform readiness and validation

✅ Recommended Screening Criteria
To help you send the right candidates quickly, prioritize profiles with:
• Proven GPU kernel development experience (non-negotiable)
• Hands-on PyTorch + Triton kernel implementation
• Evidence of systems-level programming (C/C++)
• Contributions to AI infrastructure, HPC, or compiler-level work

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