Member of Technical Staff - AI Research
About Us
Gimlet is building the first multi-silicon neocloud designed for fast, efficient inference.
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 an Member of Technical Staff focused on AI research.
As an AI Researcher, 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.
What you will work on
Monitoring and evaluating cutting-edge AI research
Researching ways to improve model accuracy, performance and efficiency
Prototyping frameworks with the latest fine-tuning and distillation techniques
You may be a good fit if
Master’s or PhD degree in computer science, engineering, applied mathematics or comparable area of study
Experience with AI/ML or applied data science.
Strong candidates may also have
Experience with PyTorch, TensorFlow, vLLM, ONNX and other AI frameworks
Software development experience with Python and C++
Understanding of the latest AI research and techniques
Strong foundation in statistical analysis
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.
Why join now?
Gimlet is at the very beginning of its journey, and that's what makes this moment special. Most AI infrastructure companies are focused on deploying more compute. We are focused on making increasingly diverse compute work together, and that ambition touches every part of how we build and run this company.
As an early member of the team, you will have significant ownership over your work, partner directly with a small group of highly capable people, and help shape not just what we build, but how we scale the company.
We value people who are excited to work across domains, take ownership of meaningful problems, and help define what Gimlet becomes over the next several years.