"kernel customization" Jobs
55 open tech roles matching “kernel customization”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Python, PyTorch, CUDA. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 55 results
Join Mirendil as a staff engineer to design and optimize custom ML kernels for frontier AI research.
Join Fastly as a Staff Software Engineer to lead Linux kernel projects and enhance performance across a global edge network.
Build and optimize low-level execution primitives for AI inference across various hardware architectures at Gimlet Labs.
Join Baseten as a Software Engineer to build and optimize microVMs for AI agents in a fast-paced, collaborative environment.
Join Baseten as a Software Engineer to optimize AI inference performance in a fast-paced startup environment.
Join Tavus as a Research Engineer to optimize cutting-edge multimodal AI models for production readiness.
Build Gimlet's AI Compiler Stack to optimize AI workloads across diverse hardware architectures.
Drive the strategy and evolution of the Calico platform as a Principal Product Manager in a hybrid role based in the San Francisco Bay Area.
Join Genmo as a GPU Performance Engineer to optimize video generation models and achieve significant performance improvements.
Characterize and improve GPU performance for AI inference at Gimlet Labs, working with a heterogeneous accelerator fleet.
Join Sesame as an ML Model Serving Engineer to enhance our serving layer for voice agents with cutting-edge techniques.
Join Anthropic as a Software Engineer to build and operate sandboxing infrastructure for AI systems at scale.
Build inference systems for AI models in production at Gimlet Labs, focusing on performance and efficiency.
Join Baseten as a Post-Training Research Engineer to build in-house tooling for efficient and high-quality machine learning models.
Join Perplexity AI as a Technical Staff member to enhance our AI inference engine with cutting-edge technologies.
Take ownership of GPU cluster infrastructure to build a self-serve platform for AI training and inference workloads.