Future Tech Jobs
Future Tech Jobs
You will architect and optimize high-performance AI inference systems, focusing on GPU kernel optimization, benchmarking, and large-scale deployment across multi-cloud environments. Collaboration with cross-functional teams and conducting original research to advance the field of ML systems are key aspects of this role.
You will architect and optimize high-performance AI inference systems, focusing on GPU kernel optimization, benchmarking, and large-scale deployment across multi-cloud environments. This role involves deep collaboration with cross-functional teams to push the boundaries of accelerated computing for AI.
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.As AI continues to shape...
This role involves leading backend engineering efforts, focusing on inter-service testing, monorepo standardization, and improving overall stability. You will work on long-term projects, evaluate impact, and collaborate across multiple teams to drive the company's technical direction and commercial success.
You will architect and optimize high-performance AI inference systems, focusing on GPU kernel optimization, compiler development, and benchmarking. Collaboration with cross-functional teams and publishing original research are key aspects of this role.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, working closely with research scientists, software engineers, and hardware experts. The focus is on improving inference speed and profiling deep learning workloads to identify and remove bottlenecks.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, working closely with research scientists, software engineers, and hardware experts. The focus is on improving inference speed and profiling deep learning workloads to identify and remove bottlenecks.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, working closely with research scientists, software engineers, and hardware experts. The focus is on improving inference speed, profiling deep learning workloads, and removing bottlenecks for NVIDIA's Cosmos platform, which is used for physical AI in autonomous vehicles, robots, and video analytics.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, working closely with research scientists, software engineers, and hardware experts. The focus is on improving inference speed and profiling deep learning workloads to identify and remove bottlenecks.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, focusing on the Cosmos World Foundation Models. You will work closely with research scientists, software engineers, and hardware experts to improve inference speed and remove bottlenecks in deep learning workloads.
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.As AI continues to shape...
As a Senior GPU Networking Architect, you will build and optimize GPU communication kernels for large-scale AI systems, focusing on minimizing latency and maximizing efficiency. You will collaborate with hardware, software, and AI teams to co-design communication strategies and contribute to the development of GPU-aware programming models.
As a Senior GPU Networking Architect, you will build and optimize GPU communication kernels for large-scale AI systems, leveraging deep knowledge of GPU architecture to improve kernel efficiency and minimize latency. You will collaborate with network software, hardware, and AI framework teams to co-design communication strategies and contribute to the evolution of GPU-aware programming models.
As a Senior GPU Networking Architect, you will develop and optimize GPU communication kernels for large-scale AI systems, focusing on minimizing latency and maximizing efficiency. You will collaborate with hardware, software, and AI teams to co-design communication strategies and contribute to the evolution of GPU-aware programming models.
As a Senior GPU Networking Architect, you will focus on building and optimizing GPU communication kernels for large-scale AI systems. Your role involves deep collaboration with network software, hardware, and AI framework teams to co-design communication strategies that align with GPU execution patterns. You will leverage your expertise in GPU architecture and CUDA programming to improve kernel efficiency, minimize latency, and develop GPU-resident communication primitives.
