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Overview Stats Perform is the market leader in sports tech. We provide the most trusted sports data to some of the world's biggest organizations, across sports, media, and broadcasting. Through the latest AI…
Build and test lightweight AI models for video analytics using PyTorch/TensorFlow, then convert them for edge deployment and benchmark performance on target hardware.
Build and own the shared AI platform that trains and serves Adobe’s generative AI models at global scale, focusing on GPU fleet utilization, low-latency inference, and end-to-end model deployment pipelines.
Develops and optimizes inference software for large language models using TensorRT-LLM, focusing on performance and scalability across platforms.
Build and optimize scalable generative AI inference pipelines and APIs for Adobe Firefly, integrating models into Photoshop, Illustrator, and other products while focusing on latency and performance.
Lead Engineer builds and deploys production-grade AI/ML models and inference pipelines for retail and operations use cases using Python, PyTorch/TensorFlow, and cloud ML tooling.
Own developer and partner adoption of NVIDIA’s Isaac GR00T end-to-end robotics workflow, guiding teams from model training to real-time deployment on Jetson Thor.
Design and scale Kubernetes-native environments for distributed robotics AI workloads, including simulation, synthetic data generation, and inference using NVIDIA frameworks like OSMO and Isaac Sim.
Build and optimize low-level compute kernels and inference pipelines for large language models running on custom ML hardware, integrating with frameworks like PyTorch and vLLM.
Builds and optimizes low-level compute kernels and serving infrastructure for large language model inference on custom ML hardware, integrating frameworks like PyTorch and vLLM.
Build and scale foundational large language models for Amazon’s shopping experiences, focusing on ML infrastructure, post-training, and reinforcement learning to improve personalization and customer interactions.
Build and optimize low-level compute kernels and serving integrations for large language model inference on custom ML hardware, spanning model execution, memory management, and distributed systems.
Leads the build-out of an internal AI/LLM platform on GPU infra: evaluates open-weight models, designs inference routers and agent tooling, and deploys scalable, observable services for corporate users.
About us We are building AI systems that can reason, use tools, and complete meaningful work in the real world. Our team works across model post-training, reinforcement-learning infrastructure, large-scale training,…
Build core data-query infrastructure for AI workloads, focusing on multimodal data (images, video, text) and distributed systems using Rust/C++/Python/Go.
Architect and deliver full-stack AI and enterprise solutions showcasing AMD GPUs/APUs, working directly with customers and internal teams to optimize inference workloads and system designs.
Develop C++ embedded software that integrates AI models into automotive systems like occupant monitoring, optimizing performance for resource-constrained hardware.
TECHNICAL MANAGER - GPU CLOUD & AI INFRASTRUCTURE Location: Singapore Employment Type: Full-Time, Permanent Monthly Salary: S$15,000-S$20,000 Reporting To: Head of GPU Cloud and AI Infrastructure Travel…
Build and optimize LM Studio’s inference runtime for on-device and cloud AI, integrating new engines and models while improving performance across CPU/GPU targets.
The Role: Build the software that lives next to—or directly inside—the robot. Munari’s edge runtime must capture and synchronize high-rate multimodal data, run local models and detection logic, manage policy execution,…
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