Systems Research Engineer Intern - GPU Programming (Fall 2026)

Together AI; San Francisco (CA); On-site; USD 79,900 - 86,788; Full time

Benefits offered by this job

Competitive compensation

Housing stipends

Other benefits

Job summary

Together AI is seeking a Systems Research Engineer Intern specialized in GPU Programming for Fall 2026. This role involves developing and optimizing GPU-accelerated kernels and collaborating with diverse teams to enhance AI system performance.

Interns will engage in extensive research and gain hands-on experience with industry-leading engineers over a 12 to 16 week program. The position offers a competitive hourly rate of $58 to $63, with additional benefits. This is an exciting opportunity to work with cutting-edge AI technologies.

Qualifications

• Strong background in GPU programming and parallel computing.
• Knowledge of ML/AI applications and models.
• Excellent problem-solving and analytical skills.

Responsibilities

• Optimize and fine-tune GPU code for better performance.
• Collaborate with teams to integrate GPU-accelerated solutions.
• Stay updated with the latest advancements in GPU programming.

Skills

GPU programming

Parallel computing

CUDA

Triton

ML/AI applications

Performance profiling tools

Analytical skills

Tools

Performance optimization tools

Job description

Systems Research Engineer Intern - GPU Programming (Fall 2026)

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 Details

Our fall internship program spans 12 to 16 weeks, where you’ll work with industry‑leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Internship dates: 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. Our team has contributed to leading open‑source research, models, and datasets to advance the frontier of AI, and 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 benefits. The estimated US hourly rate for this role is $58 to $63, adjusted 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.