Gimlet Labs is building the foundation for the next generation of AI applications. As generative AI workloads rapidly scale, inference efficiency is becoming the critical bottleneck. Gimlet is redefining AI inference from the ground up, combining cutting-edge research with an integrated hardware-software stack that delivers breakthrough performance, efficiency, and model quality.
Requirements
- Experience with AI/ML or distributed systems.
- 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
Responsibilities
- Building, deploying and scaling AI systems for production
- Evaluating and implementing cutting-edge AI research
- Researching ways to improve model accuracy, performance and efficiency
- applying the latest AI techniques to develop frameworks to help generate and optimize AI workloads
- contribute to Gimlet's novel compilation framework for partitioning and orchestrating AI workloads across diverse hardware environments
- design and implement scalable systems that can run production workloads of millions of requests a second
Other
- Currently pursuing degree in computer science, engineering, or comparable area of study
