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Gimlet Labs, Inc in San Francisco is looking for an AI Research Intern to evaluate and implement performance optimizations for AI models. You will work on cutting-edge AI research projects, exploring new model architectures and experimenting with advanced inference techniques.
The ideal candidate is pursuing a degree in computer science or engineering and has experience with AI/ML and distributed systems. Join us to shape the future of AI infrastructure in a dynamic team environment.
About Us
Gimlet is building the next generation of AI infrastructure: large-scale AI datacenters and the orchestration platform that coordinates them.
The future of AI will require vastly more compute than exists today. But as AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough. The challenge is making increasingly diverse compute work together.
Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency. Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.
We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale and help define the infrastructure layer for the future of AI.
Gimlet Labs is seeking an Member of Staff focused on AI Research (Intern). As an AI Researcher (Intern), you will be evaluating and implementing techniques to drive performance and quality optimizations across the latest AI models. The research team is responsible for exploring new model architectures and experimenting with novel inference efficiency techniques such as KV caching and FlashAttention. The team will design and prototype frameworks leveraging fine-tuning and knowledge distillation to push the boundaries of model performance.
At Gimlet, you will work on infrastructure problems that span the full stack of modern AI systems. Our team operates across datacenters, networking, distributed systems, compilers, runtimes, orchestration, and performance engineering to build the foundation for the next generation of AI infrastructure.
As an early member of the team, you will have significant ownership, work alongside highly technical engineers, and help shape both the systems we build and how we scale the company.
We value people who are excited to work across domains, take ownership of meaningful problems, and build technology that enables the next generation of AI.