About this role
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.
ABOUT THE ROLE
Gimlet Labs is seeking a Member of Technical Staff (Intern) to help develop Gimlet’s platform for deploying and monitoring AI workloads. In this role, you will be applying the latest AI techniques to develop frameworks to help generate and optimize AI workloads. You will contribute to Gimlet’s novel compilation framework for partitioning and orchestrating AI workloads across diverse hardware environments. You will design and implement scalable systems that can run production workloads of millions of requests a second.
WHAT YOU WILL WORK ON
- Building, deploying and scaling AI systems for production
- Evaluating and implementing cutting-edge AI research
- Researching ways to improve model accuracy, performance and efficiency
YOU MAY BE A GOOD FIT IF
- Currently pursuing degree in computer science, engineering, or comparable area of study
- Experience with AI/ML or distributed systems.
STRONG CANDIDATES MAY ALSO HAVE
- Experience with PyTorch, TensorFlow, ONNX and other AI frameworks
- Familiarity with distributed systems and orchestration frameworks (e.g., Kubernetes)
- Software development experience with Python and C++
- Understanding of the latest AI research and techniques
WHAT MAKES GIMLET DIFFERENT
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.
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.
ABOUT THE ROLE
Gimlet Labs is seeking a Member of Technical Staff (Intern) to help develop Gimlet’s platform for deploying and monitoring AI workloads. In this role, you will be applying the latest AI techniques to develop frameworks to help generate and optimize AI workloads. You will contribute to Gimlet’s novel compilation framework for partitioning and orchestrating AI workloads across diverse hardware environments. You will design and implement scalable systems that can run production workloads of millions of requests a second.
WHAT YOU WILL WORK ON
- Building, deploying and scaling AI systems for production
- Evaluating and implementing cutting-edge AI research
- Researching ways to improve model accuracy, performance and efficiency
YOU MAY BE A GOOD FIT IF
- Currently pursuing degree in computer science, engineering, or comparable area of study
- Experience with AI/ML or distributed systems.
STRONG CANDIDATES MAY ALSO HAVE
- Experience with PyTorch, TensorFlow, ONNX and other AI frameworks
- Familiarity with distributed systems and orchestration frameworks (e.g., Kubernetes)
- Software development experience with Python and C++
- Understanding of the latest AI research and techniques
WHAT MAKES GIMLET DIFFERENT
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.
Tech stack
PyTorchTensorFlowKubernetesPythonC++
About Gimlet Labs
Gimlet Labs is hiring for the member of technical staff role. NewJob aggregates active openings directly from Gimlet Labs's applicant tracking system, so this listing is current.
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