Systems Research Engineer Intern - GPU Programming (Fall 2026)

Together AI
San Francisco, US
On-site

Who this role is best for

Geared toward mid-level candidates with GPU programming expertise who thrive in collaborative research environments focused on AI infrastructure.

Best fit for

  • Candidates with hands-on CUDA/Triton experience optimizing ML workloads
    — “Strong background in GPU programming and parallel computing, such as CUDA and/or Triton
  • Researchers who bridge hardware-software gaps in AI systems
    — “contribute to the co-design of efficient GPU architectures and programming models
  • Performance engineers comfortable with cross-team kernel optimization
    — “Collaborate with cross-functional teams to integrate GPU-accelerated solutions

Things to consider

  • 12-16 week commitment during specified fall dates
    — “Our fall internship program spans over 12 to 16 weeks

How to stand out

  • Show concrete examples of kernel optimization impact
    — “Optimize and fine-tune GPU code to achieve better performance
  • Highlight open-source contributions to AI infrastructure projects
    — “possibly contribute to influential open source projects
  • Demonstrate knowledge of cutting-edge GPU profiling tools
    — “Knowledge of performance profiling and optimization tools for GPU programming
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Intern

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Optimized GPU-accelerated kernels and algorithms
  • Integrated GPU-accelerated solutions into existing software systems
Typical background
Master's or PhD in Computer Science, Electrical Engineering, or related field

Skills & requirements

Required

GPU ProgrammingCUDATritonMl/ai ApplicationsParallel ComputingPerformance Profiling

Preferred

Triton

Stack & domain

CudaTritonMl/ai Applications And ModelsPerformance Profiling And Optimization Tools For Gpu ProgrammingProblem-solvingAnalytical SkillsAIMLGpu Programming

About the role

Original posting from Together AI via Greenhouse

About The Role

As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.

Responsibilities

Optimize and fine-tune GPU code to achieve better performance and scalability

Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems

Stay up-to-date with the latest advancements in GPU programming techniques and technologies

Requirements

Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.

Knowledge of ML/AI applications and models

Knowledge of performance profiling and optimization tools for GPU programming

Excellent problem-solving and analytical skills

Internship Program Details

Our fall internship program spans over 12 to 16 weeks where you’ll have the opportunity to work with industry-leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Our internship dates are September 14th to December 18th. 

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Mamba, FlexGen, Petals, Mixture of Agents, and RedPajama.

Compensation

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $63. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

 

Source: Together AI careers (Greenhouse)

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