About the role#
As a Systems Research Engineer Intern, you will focus on GPU programming to build and improve kernels for AI and ML applications. You will work with the modeling and algorithm teams to co-design GPU kernels and model architectures. This role involves working with both hardware and software teams to create efficient architectures and programming models. You will work on-site at our San Francisco headquarters during the Winter 2027 term, from January 4th to April 9th.
What you'll do#
- Develop and optimize GPU-accelerated kernels and algorithms.
- Co-design GPU kernels and model architecture.
- Contribute to the design of efficient GPU architectures and programming models.
- Optimize and fine-tune GPU code for better performance and scalability.
- Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems.
- Research and track the latest advancements in GPU programming techniques.
What you'll need#
- A strong background in GPU programming and parallel computing, specifically CUDA or Triton.
- Knowledge of ML and AI applications and models.
- Familiarity with performance profiling and optimization tools for GPU programming.
- Excellent problem-solving and analytical skills.
- Current enrollment in a Computer Science, Computer Engineering, or Electrical Engineering program.
Location & details#
- Location: San Francisco, California.
- Term: Winter 2027 (January 4th to April 9th).
- Modality: On-site.
- Employment: Full-time internship.
- Compensation: $58 to $70 per hour, including housing stipends.
About Together AI
Together AI operates a cloud platform for AI engineers and researchers. The company provides tools for inference, model shaping, and pre-training. Founded in 2022, it maintains its headquarters in San Francisco, California. The organization employs 415 people and serves clients ranging from AI startups to SaaS companies.
How to get in at Together AI
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