Systems Research Engineer Intern - GPU Programming (Summer 2027)

Togetherai; San Francisco (CA); On-site; USD 80,000 - 96,000; Part time

Benefits offered by this job

Housing stipend

Competitive compensation

Job summary

Together AI is seeking a Systems Research Engineer Intern specialized in GPU Programming to develop and optimize GPU-accelerated kernels for ML/AI applications. You will co-design GPU kernels and model architectures, collaborating with hardware and software teams to advance efficient GPU programming models.

You will stay current with the latest GPU programming techniques and contribute to AI infrastructure innovations, aligning with industry-leading engineering practices.

Qualifications

• 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.

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.

Skills

CUDA

Triton

ML/AI models

Profiling tools

Problem-solving

Job description

Role Overview

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

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Internship Program Details:

Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading engineers and researchers across multiple teams. This cohort's internship dates span either May 17th to August 6th or June 14th to September 3rd.

Compensation

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $70 an hour. 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